View source for Snowflake Inc. patent applications published on December 14th, 2023

==Patent applications for Snowflake Inc. on December 14th, 2023==

===SEMANTIC FUNCTIONAL WRAPPERS OF SERVICES ([[18454555. SEMANTIC FUNCTIONAL WRAPPERS OF SERVICES simplified abstract (Snowflake Inc.)|18454555]])===


'''Main Inventor'''

Tom L. Button


'''Brief explanation'''
 The abstract of this patent application describes functional wrappers, which are scripts and software that group and invoke specific functionality in a legacy application. These wrappers allow access to legacy application functionality in modern software architectures without the risk of errors during the porting process. The abstract also mentions the addition of functionality to the wrappers, such as parallelism and scaling, which were not available when the legacy applications were developed. The automatic generation of these functional wrappers is also disclosed.

* Functional wrappers are scripts/software that group and invoke specific functionality in a legacy application.
* They provide programmatic access to legacy application functionality in modern software architectures.
* They eliminate the risk of errors during the porting process.
* Additional functionality, like parallelism and scaling, can be added to the wrappers.
* The patent application discloses the automatic generation of these functional wrappers.

== Potential Applications ==
* Integration of legacy applications into modern software architectures.
* Enabling programmatic access to specific functionality in legacy applications.
* Adding new features to legacy applications without modifying their codebase.

== Problems Solved ==
* Risk of errors during the porting process of legacy applications.
* Limited access to specific functionality in legacy applications.
* Inability to add new features to legacy applications without modifying their codebase.

== Benefits ==
* Seamless integration of legacy applications into modern software architectures.
* Improved access to specific functionality in legacy applications.
* Ability to add new features to legacy applications without modifying their codebase.
* Automatic generation of functional wrappers saves time and effort.

'''Abstract'''
 Functional wrappers are scripts and related software that provide a way to group and invoke functionality comprising semantic intent in a legacy application. These functional wrappers allow programmatic access to functionality in legacy applications in contemporary software architectures without risk of porting errors. Additional functionality to provide features with presently expected, but not available at the time the legacy applications were developed, such as functional wrappers to provide parallelism and scaling, are disclosed. Finally, automatic generation of the functional wrappers are also disclosed.

===SCHEMA EVOLUTION ([[18345987. SCHEMA EVOLUTION simplified abstract (Snowflake Inc.)|18345987]])===


'''Main Inventor'''

Istvan Cseri


'''Brief explanation'''
 ==Abstract==
Techniques for detecting and handling schema mismatches in data uploading are disclosed. The schema of the data to be uploaded is compared with the schema of the source table. If a mismatch is found, the schema of the source table can be modified to accommodate the new data without losing any existing data.

==Bullet Points==
* The patent application describes techniques for detecting and handling schema mismatches during data uploading.
* It involves comparing the schema of the data to be uploaded with the schema of the source table.
* If a mismatch is detected, the schema of the source table can be modified to accommodate the new data.
* This allows the upload process to continue without any loss of existing data.

==Potential Applications==
* Database management systems
* Data integration platforms
* E-commerce platforms
* Data warehousing systems

==Problems Solved==
* Schema mismatches during data uploading can cause data loss or errors.
* Modifying the schema of the source table manually can be time-consuming and error-prone.
* Existing solutions may not handle schema evolution efficiently.

==Benefits==
* Prevents data loss during data uploading by detecting and handling schema mismatches.
* Automates the modification of the source table schema to accommodate new data.
* Saves time and reduces errors by eliminating the need for manual schema modifications.
* Enables efficient schema evolution in database management systems.

'''Abstract'''
 Techniques for schema mismatch detection and evolution are described. When data is being uploaded into a source table, schema of the data to be uploaded can be compared with the schema for the source table. If a schema mismatch is detected, the schema of the source table can be modified, and the upload can be continued without data loss.

===SIMILARITY-BASED LISTING RECOMMENDATIONS IN A DATA EXCHANGE ([[18112934. SIMILARITY-BASED LISTING RECOMMENDATIONS IN A DATA EXCHANGE simplified abstract (Snowflake Inc.)|18112934]])===


'''Main Inventor'''

Orestis Kostakis


'''Brief explanation'''
 The abstract describes a method for determining affinity metrics for a set of listings in a data exchange. Affinity metrics are characteristics that help identify listings with similar characteristics. An affinity score is calculated for each pair of listings using these metrics and stored in an affinity store. The affinity score is then used to present listings that have a high affinity with a particular listing.

* Affinity metrics are determined for a set of listings in a data exchange.
* Affinity metrics help identify listings with similar characteristics.
* An affinity score is calculated for each pair of listings using the affinity metrics.
* The affinity score is stored in an affinity store.
* Listings with high affinity scores are presented based on their similarity to a particular listing.

==Potential Applications==
* This technology can be applied in online marketplaces to recommend similar listings to users based on their preferences.
* It can be used in social networking platforms to suggest connections or friends with similar interests.
* The method can be utilized in content recommendation systems to provide personalized suggestions based on user preferences.

==Problems Solved==
* The technology solves the problem of efficiently identifying and presenting listings with similar characteristics in a data exchange.
* It addresses the challenge of providing personalized recommendations to users based on their preferences.
* The method solves the issue of manually searching for similar listings by automating the process using affinity metrics and scores.

==Benefits==
* Users can easily discover and explore listings that match their preferences without extensive searching.
* The technology improves user experience by providing personalized recommendations.
* It saves time and effort for users by automating the process of finding similar listings.
* The method enhances the efficiency of data exchanges by facilitating the identification and presentation of relevant listings.

'''Abstract'''
 A set of affinity metrics may be determined for a set of listings, each listing of the set of listings comprising data to be shared through a data exchange, wherein the set of affinity metrics includes a set of characteristics allowing identification of a listing having one or more characteristics in the set of characteristics. For each pair of listings of the set of listings, an affinity score can be calculated, using the set of affinity metrics, and stored as part of the record in an affinity store. One or more listings of the set of listings using the affinity score between the first listing of the set of listings and the one or more listings of the set of listings can be presented.

===QUERY PROCESSING USING HYBRID TABLE SECONDARY INDEXES ([[18171296. QUERY PROCESSING USING HYBRID TABLE SECONDARY INDEXES simplified abstract (Snowflake Inc.)|18171296]])===


'''Main Inventor'''

Nikolaos Romanos Katsipoulakis


'''Brief explanation'''
 The subject technology described in the patent application is a method for performing read and write operations on database tables while ensuring data consistency and avoiding conflicts. Here is a simplified explanation of the abstract:

* The technology obtains a timestamp for a first transaction.
* It performs a read operation on a parent table associated with the transaction to determine the committed versions of the table.
* It checks if a specific key exists in the parent table based on the transaction.
* If the key exists, it performs a write operation on a child table.
* It checks if there is a duplicate key in the child table.
* If there is no duplicate key, it checks if there is a conflict with the key.
* If there is no conflict, it performs a write operation on a secondary index table of the child table.

Potential applications of this technology:

* Database management systems
* Transaction processing systems
* Distributed databases

Problems solved by this technology:

* Ensures data consistency by checking committed versions of tables before performing write operations
* Avoids conflicts and duplicate keys in the database
* Provides a mechanism for maintaining secondary index tables

Benefits of this technology:

* Improved data integrity and consistency in database operations
* Efficient handling of read and write operations in a transactional environment
* Simplified management of database tables and indexes

'''Abstract'''
 The subject technology obtains a read timestamp of a first transaction. The subject technology performs a first read operation on a parent table associated with the first transaction to determine a set of committed versions of the parent table. The subject technology determines whether a key exists in the parent table based on the first transaction. The subject technology, in response to the key existing in the parent table, performs a first write operation on a child table. The subject technology determines whether a duplicate key exists in the child table. The subject technology, in response to determining that there is no duplicate key in the child table, determines whether there is a conflict with the key. The subject technology, in response to determining that there is no conflict with the key, performs a second write operation on a secondary index table of the child table.

===PROVIDING TABLE DATA ACCESS IN USER-SPECIFIED FORMATS ON USER-MANAGED STORAGE ([[18193069. PROVIDING TABLE DATA ACCESS IN USER-SPECIFIED FORMATS ON USER-MANAGED STORAGE simplified abstract (Snowflake Inc.)|18193069]])===


'''Main Inventor'''

Selcuk Aya


'''Brief explanation'''
 The subject technology described in the patent application is a system that allows for the conversion and storage of tables in different formats on external volumes. Here is a simplified explanation of the abstract:

* The technology receives a command to convert a table into a different format and store it on an external volume.
* It creates a snapshot of the table on internal storage for reference.
* It generates a list of metadata files on the internal storage to keep track of the table's properties.
* Based on the list of metadata files, it generates a set of metadata files on the internal storage to provide additional information about the table.
* It then creates a second snapshot of the table on the external volume to ensure data integrity.
* It generates a second list of metadata files on the external volume to keep track of the table's properties on the external volume.
* Based on the second list of metadata files, it generates a second set of metadata files on the external volume to provide additional information about the table on the external volume.
* Finally, it creates a set of data files in a different file format on the external volume.

Potential applications of this technology:

* Data migration: This technology can be used to convert and store tables in different formats on external volumes, making it useful for data migration between different systems or platforms.
* Data backup and recovery: By creating snapshots and metadata files, this technology enables efficient backup and recovery of tables, ensuring data integrity and minimizing the risk of data loss.
* Data analysis: The ability to convert tables into different formats on external volumes can facilitate data analysis by allowing for compatibility with various analytical tools and software.

Problems solved by this technology:

* Format conversion: The technology addresses the challenge of converting tables into different formats, which is often required when working with different systems or software that have specific format requirements.
* Data integrity: By creating snapshots and metadata files, the technology ensures that the converted tables on the external volume are accurate and complete, reducing the risk of data corruption or loss.
* Storage efficiency: The use of snapshots and metadata files optimizes storage space by only storing the necessary information for the converted tables, reducing redundancy.

Benefits of this technology:

* Flexibility: The ability to convert tables into different formats allows for greater flexibility in working with data across different systems or software.
* Data protection: The creation of snapshots and metadata files ensures data integrity and provides a reliable backup and recovery solution.
* Storage optimization: By generating metadata files and only storing necessary information, the technology optimizes storage space and reduces storage costs.

'''Abstract'''
 The subject technology receives a command to commit a table in a different table format on an external volume. The subject technology generates a first snapshot of the table on internal storage. The subject technology generates a first list of metadata files on the internal storage. The subject technology generates, based on the first list of metadata files, a first set of metadata files on the internal storage. The subject technology generates a second snapshot of the table on the external volume. The subject technology generates a second list of metadata files on the external volume. The subject technology generates, based on the second list of metadata files, a second set of metadata files on the external volume. The subject technology generates a first set of data files in a different file format on the external volume.

===AUTO REFRESH OF DIRECTORY TABLES FOR STAGES ([[18341453. AUTO REFRESH OF DIRECTORY TABLES FOR STAGES simplified abstract (Snowflake Inc.)|18341453]])===


'''Main Inventor'''

Polita Paulus


'''Brief explanation'''
 The abstract describes a method for managing file stages in a database platform. Here is a simplified explanation of the abstract:

* The method involves creating a file stage in a user account on a database platform, along with a hidden stage directory table and a data pipeline for the file stage.
* The data pipeline is then linked to the file stage.
* When an event occurs in the file stage, a notification is received.
* The corresponding data pipeline is identified and the hidden stage directory table is updated.

Potential applications of this technology:

* Database management systems can utilize this method to efficiently handle file stages and data pipelines.
* It can be used in various industries that rely on database platforms, such as finance, healthcare, and e-commerce.

Problems solved by this technology:

* Simplifies the process of managing file stages in a database platform.
* Provides a streamlined approach to handle events and update relevant data pipelines.
* Enhances the overall efficiency and performance of database management systems.

Benefits of this technology:

* Improved organization and management of file stages in a user account.
* Faster and more accurate identification of data pipelines associated with file stages.
* Real-time notifications enable prompt action and updates to the hidden stage directory table.
* Enhances the reliability and effectiveness of database platforms.

'''Abstract'''
 In one aspect, a method includes forming, at a database platform, a file stage in a user account on the database platform, the user account being associated with a client, forming, at the database platform, a hidden stage directory table and a data pipeline for the file stage, and binding the data pipeline to the file stage. The method also includes receiving a notification of an event of the file stage. The method also includes identifying the data pipeline corresponding to the file stage. The method also includes updating the hidden stage directory table of the identified data pipeline.

===QUERY EXECUTION USING MATERIALIZED TABLES ([[18353317. QUERY EXECUTION USING MATERIALIZED TABLES simplified abstract (Snowflake Inc.)|18353317]])===


'''Main Inventor'''

Tyler Arthur Akidau


'''Brief explanation'''
 The abstract describes a method for scheduling refresh operations on materialized tables (MTs) based on their lag duration and the number of prior refreshes. 

* The method involves retrieving a set of MTs, each with a lag duration and referring to a base table.
* Lag duration indicates the maximum time period that a prior refresh of a query on the base table can lag behind the current time.
* The method determines multiple time instances for each MT based on the lag duration and the number of prior refreshes of the base table.
* Aligned time instances for all the MTs are determined based on the multiple time instances for each MT.
* Refresh operations are scheduled for the MTs at the aligned time instances that fall within the maximum time period.

==Potential Applications==
* Database management systems
* Data warehousing
* Business intelligence systems

==Problems Solved==
* Efficient scheduling of refresh operations for materialized tables
* Ensuring that the results of queries on base tables are up-to-date within a specified lag duration

==Benefits==
* Improved performance and efficiency in data processing
* Timely availability of refreshed data for analysis and decision-making

'''Abstract'''
 A method includes retrieving a plurality of materialized tables (MTs). Each of the plurality of MTs includes a lag duration and refers to a corresponding base table of a plurality of base tables. The lag duration indicates a maximum time period that a result of a prior refresh of a query on the corresponding base table can lag behind a current time instance. A plurality of time instances for the MT is determined based on the lag duration and a number of prior refreshes of the corresponding base table. A plurality of aligned time instances for the plurality of MTs is determined based on the plurality of time instances for each of the plurality of MTs. Refresh operations are scheduled for the plurality of MTs at one or more of the plurality of aligned time instances that are within the maximum time period.

===DATA CLEAN ROOM USING DEFINED ACCESS VIA NATIVE APPLICATIONS ([[17816420. DATA CLEAN ROOM USING DEFINED ACCESS VIA NATIVE APPLICATIONS simplified abstract (Snowflake Inc.)|17816420]])===


'''Main Inventor'''

Rachel Frances Blum


'''Brief explanation'''
 The present disclosure describes a data sharing system implemented as a local application of a distributed database. This system allows for the validation and execution of queries against a shared dataset that includes data from the database dataset as well as additional data from another database within the distributed database.

* The system is implemented as a local application of a distributed database.
* Queries from a query template are validated and executed against a shared dataset.
* The shared dataset includes portions of data from the database dataset and additional portions of data from another database within the distributed database.

==Potential Applications==
* Collaborative data analysis: Multiple users can access and analyze data from different databases within the distributed database, enabling collaboration and knowledge sharing.
* Data integration: The system allows for the integration of data from multiple databases, making it easier to combine and analyze information from different sources.
* Distributed data management: The system provides a way to manage and share data across multiple databases in a distributed environment.

==Problems Solved==
* Data silos: The system helps overcome the problem of data being stored in separate databases, making it difficult to access and analyze information from different sources.
* Data inconsistency: By allowing for the integration of data from multiple databases, the system helps ensure consistency and accuracy of the shared dataset.
* Collaboration barriers: The system enables collaboration and knowledge sharing by allowing users to access and analyze data from different databases within the distributed database.

==Benefits==
* Improved data accessibility: Users can easily access and analyze data from multiple databases within the distributed database, eliminating the need to manually search and combine information from different sources.
* Enhanced data analysis: The system allows for the integration of data from multiple databases, enabling more comprehensive and insightful analysis.
* Efficient collaboration: Users can collaborate and share knowledge by accessing and analyzing data from different databases within the distributed database, promoting teamwork and innovation.

'''Abstract'''
 Embodiments of the present disclosure may provide a data sharing system implemented as a local application of a distributed database. A query from a query template can be validated and executed against shared dataset that comprises portions of data from the database dataset and additional portions of data from another database of the distributed database.

===QUERY VALIDATION AND PROCESSING IN DATA CLEAN ROOMS ([[18162710. QUERY VALIDATION AND PROCESSING IN DATA CLEAN ROOMS simplified abstract (Snowflake Inc.)|18162710]])===


'''Main Inventor'''

Rachel Frances Blum


'''Brief explanation'''
 The abstract describes a method for securely sharing data between a provider and a consumer in a database system. Here is a simplified explanation of the abstract:

* The method involves creating a secure environment called a "clean room" in the provider's database account.
* An application instance is installed in the consumer's account, which allows access to the clean room.
* The provider shares their data with the clean room, making it accessible to the consumer through the application instance.
* The provider also shares a query template with the consumer through the application instance.
* The consumer generates a query based on the template, and the system validates it.
* The query is executed, and the results are stored in the consumer's database account.

Potential applications of this technology:

* Secure data sharing between different parties in a database system.
* Collaborative data analysis where sensitive data needs to be protected.
* Controlled access to specific data sets within a database.

Problems solved by this technology:

* Ensuring data privacy and security when sharing sensitive information.
* Allowing controlled access to specific data without exposing the entire database.
* Enabling collaboration and analysis while maintaining data integrity.

Benefits of this technology:

* Enhanced data security through the use of clean rooms and controlled access.
* Efficient and streamlined data sharing process between providers and consumers.
* Improved collaboration and analysis capabilities while protecting sensitive data.

'''Abstract'''
 A method includes generating a defined access clean room in a provider database account, as well as installing, in a consumer account, an application instance that implements the defined access clean room. The method also includes sharing, by the provider database account, source provider data with the defined access clean room, where the sharing makes the source provider data accessible to the consumer database account via the application instance. The method further includes sharing, by the provider database account, a query template with the consumer database account via the application instance. Additionally, the method includes receiving a query generated by the consumer database account based on the query template, validating that the query is consistent with the query template, responsively generating query results by executing the query, as well as storing the query results in the consumer database account.

===REPLICATION OF UNSTRUCTURED STAGED DATA BETWEEN DATABASE DEPLOYMENTS ([[18051657. REPLICATION OF UNSTRUCTURED STAGED DATA BETWEEN DATABASE DEPLOYMENTS simplified abstract (Snowflake Inc.)|18051657]])===


'''Main Inventor'''

Robert Bengt Benedikt Gernhardt


'''Brief explanation'''
 The abstract of the patent application describes a method for implementing unstructured data replication in a distributed database. The replication can be done using either an internal or external storage location. The process involves replicating metadata, such as a directory table, followed by replicating the staged data. The replication of staged data can be achieved by replicating either the stage metadata or the database files between different deployments.

* The patent application describes a method for replicating unstructured data in a distributed database.
* The replication can be done using either internal or external storage.
* Metadata, such as a directory table, is replicated across different deployments.
* The staged data is then replicated, either by replicating the stage metadata or the database files.
* This method allows for efficient replication of unstructured data in a distributed database.

==Potential Applications==
* This technology can be applied in cloud computing environments where distributed databases are used.
* It can be used in systems that require replication of unstructured data across multiple locations.
* The method can be implemented in data-intensive applications that deal with large volumes of unstructured data.

==Problems Solved==
* The technology solves the problem of efficiently replicating unstructured data in a distributed database.
* It addresses the challenge of replicating metadata and staged data across different deployments.
* The method provides a solution for replicating unstructured data without impacting the performance of the database.

==Benefits==
* The technology enables efficient replication of unstructured data, improving data availability and reliability.
* It allows for easy scalability of distributed databases by replicating data across multiple deployments.
* The method provides flexibility in choosing the replication approach, either replicating stage metadata or database files.

'''Abstract'''
 The distributed database can implement unstructured data replication using an internal or external storage location. Metadata, such as a directory table that lists the unstructured files, can be replicated across different deployments, followed by replication of the staged data. Replicating the staged data can be implemented by replication of only the stage metadata or replication of the database files between the deployments.

===CROSS-CLOUD REPLICATION OF RECURRENTLY EXECUTING DATA PIPELINES ([[17823752. CROSS-CLOUD REPLICATION OF RECURRENTLY EXECUTING DATA PIPELINES simplified abstract (Snowflake Inc.)|17823752]])===


'''Main Inventor'''

Istvan Cseri


'''Brief explanation'''
 The patent application describes a computer-implemented method for replicating recurrently executed tasks from one data pipeline to another data pipeline hosted on different cloud services. 

* The method involves detecting a committed version of recurrently executed tasks on a primary deployment hosted on a first cloud service.
* The committed version of the tasks is then replicated to a secondary deployment hosted on a second cloud service.
* The replication ensures that both data pipelines have the same version of the recurrently executed tasks.

==Potential Applications==
* Data replication and synchronization between different cloud services.
* Ensuring consistency and reliability of recurrently executed tasks across multiple deployments.
* Facilitating disaster recovery and backup strategies for data pipelines.

==Problems Solved==
* Ensures that recurrently executed tasks are replicated accurately and consistently across different cloud services.
* Provides a solution for maintaining data pipeline integrity and reliability in multi-cloud or hybrid cloud environments.
* Simplifies the process of replicating and synchronizing data pipelines hosted on different cloud services.

==Benefits==
* Improved data pipeline reliability and consistency.
* Enhanced disaster recovery capabilities for data pipelines.
* Flexibility to host data pipelines on different cloud services while maintaining synchronization.
* Simplified management and maintenance of data pipelines in multi-cloud or hybrid cloud environments.

'''Abstract'''
 In one aspect, a computer-implemented method includes detecting a committed version of recurrently executed tasks of a first data pipeline on a primary deployment that is hosted on a first cloud service, and replicating the committed version of the recurrently executed tasks to a second data pipeline on a secondary deployment that is hosted on a second cloud service.

===LOW LATENCY INGESTION INTO A DATA SYSTEM ([[18456675. LOW LATENCY INGESTION INTO A DATA SYSTEM simplified abstract (Snowflake Inc.)|18456675]])===


'''Main Inventor'''

Dhiraj Gupta


'''Brief explanation'''
 Described in this patent application are techniques for enhancing the transfer of metadata from a metadata database to a data system's database, such as a data warehouse. The metadata is stored in the metadata database with a version stamp and a partition identifier. Multiple readers can scan the metadata database based on these values to export the metadata to a cloud storage location. The exported data can then be automatically ingested into the database, which includes a journal and snapshot table.

* Techniques for improving transfer of metadata from a metadata database to a data system's database
* Metadata is stored in the metadata database with a version stamp and a partition identifier
* Multiple readers can scan the metadata database based on version stamp and partition identifier values
* Exported metadata is stored in a cloud storage location
* Exported data is automatically ingested into the database, which includes a journal and snapshot table

== Potential Applications ==
* Data warehousing
* Database management systems
* Cloud storage and data transfer

== Problems Solved ==
* Efficient transfer of metadata from a metadata database to a data system's database
* Simplified export and ingestion process
* Improved organization and management of metadata

== Benefits ==
* Streamlined transfer process reduces manual effort and potential errors
* Faster and more efficient data transfer and ingestion
* Improved organization and accessibility of metadata

'''Abstract'''
 Described herein are techniques for improving transfer of metadata from a metadata database to a database stored in a data system, such as a data warehouse. The metadata may be written into the metadata database with a version stamp, which is monotonic increasing register value, and a partition identifier, which can be generated using attribute values of the metadata. A plurality of readers can scan the metadata database based on version stamp and partition identifier values to export the metadata to a cloud storage location. From the cloud storage location, the exported data can be auto ingested into the database, which includes a journal and snapshot table.

===HYBRID TABLE SECONDARY INDEX FOR LOOKUPS, UNIQUE CHECKS, AND REFERENTIAL INTEGRITY CONSTRAINTS ([[18171292. HYBRID TABLE SECONDARY INDEX FOR LOOKUPS, UNIQUE CHECKS, AND REFERENTIAL INTEGRITY CONSTRAINTS simplified abstract (Snowflake Inc.)|18171292]])===


'''Main Inventor'''

Nikolaos Romanos Katsipoulakis


'''Brief explanation'''
 The subject technology described in this patent application involves a system that receives information from a metadata database related to a base table. It then determines a table object associated with the base table and generates a nested object based on additional metadata. This nested object is linked to the table object. 

* The system also generates a second table object that represents a secondary index of the base table and includes information linking it to the nested object.
* A link is established between the second table object and the base table based on the nested object.
* The nested object and the second table object are stored in the metadata database.

==Potential Applications==
* This technology can be applied in database management systems to improve indexing and organization of data.
* It can be used in data analysis and data mining applications to enhance the efficiency of searching and retrieving information.

==Problems Solved==
* The technology solves the problem of efficiently organizing and indexing large amounts of data in a database.
* It addresses the challenge of linking and managing nested objects within a database system.

==Benefits==
* Improved performance and efficiency in searching and retrieving data from a database.
* Enhanced organization and indexing of data, leading to faster data processing.
* Simplified management of nested objects within a database system.

'''Abstract'''
 The subject technology receives, from a metadata database, information related to a base table. The subject technology determines a table object associated with the base table, the table object including a first set of metadata. The subject technology generates a nested object based on a second set of metadata, the second set of metadata including information linking the nested object to the table object. The subject technology generates a second table object associated with the nested object, the second table object representing a secondary index of the base table, the second table object including information linking the second table object to the nested object. The subject technology establishes a link between the second table object to the base table based on the nested object. The subject technology stores, in the metadata database, the nested object and the second table object.

===PROJECTION CONSTRAINTS IN A QUERY PROCESSING SYSTEM ([[17934814. PROJECTION CONSTRAINTS IN A QUERY PROCESSING SYSTEM simplified abstract (Snowflake Inc.)|17934814]])===


'''Main Inventor'''

Khalid Zaman Bijon


'''Brief explanation'''
 '''Abstract:'''
A constraint system is used to enforce projection constraints on data values stored in specific columns of a shared dataset when queries are received by a database system. These projection constraints restrict the presentation or output of data in response to a query, while still allowing certain operations to be performed on the data and providing a corresponding output. The constraints can be triggered based on various contexts, such as the user submitting the query. This approach enables the sharing and use of data anonymously without the need for data tokenization.

* The patent application describes a constraint system for enforcing projection constraints on data values in a shared dataset.
* Projection constraints restrict the presentation or output of data in response to queries.
* The constraints allow specified operations to be performed on the data and provide a corresponding output.
* The constraints can be triggered based on various contexts, such as the user submitting the query.
* This approach enables the sharing and use of data anonymously without the need for data tokenization.

'''Potential Applications:'''
* Data sharing platforms that require anonymity while allowing certain operations on shared data.
* Collaborative databases where users can perform operations on shared data without revealing sensitive information.
* Research databases that allow researchers to access and analyze data while protecting the privacy of individuals.

'''Problems Solved:'''
* Ensures privacy and anonymity of shared data by restricting its presentation or output.
* Allows for the use of shared data without the need to tokenize or anonymize it.
* Enables controlled access to sensitive data while still allowing useful operations to be performed.

'''Benefits:'''
* Protects the privacy of individuals by restricting the presentation or output of shared data.
* Simplifies the sharing and use of data by eliminating the need for data tokenization.
* Enables secure and controlled access to sensitive data for authorized operations.

'''Abstract'''
 A constraint system enforces projection constraints on data values stored in specified columns of a shared dataset when queries are received by a database system. A projection constraint identifies that the data in a column may be restricted from being projected (e.g., presented, read, outputted) in an output to a received query, while allowing specified operations to be performed on the data and a corresponding output to be provided. For example, the projection constraint may indicate a context for a query that triggers the constraint, such as based on the user that submitted the query. Enforcing projection constraints on queries received at the database system allows for data to be shared and used anonymously by entities to perform various operations without the need to tokenize the data.

===ENHANCED TIME SERIES FORECASTING ([[18112944. ENHANCED TIME SERIES FORECASTING simplified abstract (Snowflake Inc.)|18112944]])===


'''Main Inventor'''

Michel Adar


'''Brief explanation'''
 Using an attributes model, this patent application proposes a time series forecasting model that determines a set of features based on time series data, including periodic components. The data can be divided into segments, and each segment can be assigned a weight based on its age. This results in a set of weighted segments of time series data. 

The patent application also introduces a trend detection model that analyzes the weighted segments to determine trend data. By combining the set of features and the trend data, a time series forecast can be generated. 

* The patent application proposes a time series forecasting model based on an attributes model.
* The model determines a set of features from time series data, including periodic components.
* The time series data can be divided into segments, and each segment is assigned a weight based on its age.
* The weighted segments of time series data are analyzed using a trend detection model to determine trend data.
* The set of features and trend data are combined to generate a time series forecast.

==Potential Applications==
This technology has potential applications in various fields, including:

* Financial forecasting: Predicting stock prices, market trends, and economic indicators.
* Demand forecasting: Forecasting product demand, optimizing inventory management, and supply chain planning.
* Energy forecasting: Predicting energy consumption, optimizing energy production, and grid management.
* Weather forecasting: Forecasting weather patterns, improving climate models, and disaster preparedness planning.

==Problems Solved==
This technology addresses several problems in time series forecasting, such as:

* Incorporating periodic components: By considering periodic components in the set of features, the model can capture recurring patterns in the data.
* Weighting segments based on age: Assigning weights to segments based on their age helps prioritize recent data, which may be more relevant for forecasting.
* Trend detection: The trend detection model allows for the identification of underlying trends in the data, enabling more accurate forecasts.

==Benefits==
The benefits of this technology include:

* Improved accuracy: By considering both periodic components and trend data, the time series forecasts generated by this model are expected to be more accurate.
* Flexibility: The model can be applied to various types of time series data and can adapt to different forecasting needs.
* Efficiency: The use of weighted segments and trend detection helps optimize the forecasting process, reducing computational time and resources required.

'''Abstract'''
 Using an attributes model of a time series forecasting model, determine a set of features based on time series data, the set of features including periodic components. The time series data may be divided into a set of segments. For each segment of the set of segments, a weight may be assigned using an age of the segment, resulting in a set of weighted segments of time series data. Using a trend detection model of the time series forecasting model, trend data from the set of weighted segments of time series data may be determined. A time series forecast may be generated by combining the set of features and the trend data.

===USER INTERFACE FRAMEWORK FOR WEB APPLICATIONS ([[18187031. USER INTERFACE FRAMEWORK FOR WEB APPLICATIONS simplified abstract (Snowflake Inc.)|18187031]])===


'''Main Inventor'''

Damien Carru


'''Brief explanation'''
 The abstract describes a data platform that allows an application to be managed as a database object. The application can include User Interface (UI) components and can be shared by a provider account to multiple consumer accounts. The sharing is done through a share object and grant commands. The consumer accounts can deploy and operate the UI component based on the shared object.

* The data platform manages applications as first-class database objects.
* Applications can include UI components.
* Provider accounts can share applications with consumer accounts.
* Sharing is done through a share object and grant commands.
* Consumer accounts can deploy and operate the shared UI components.

==Potential Applications==
* Collaborative software development platforms.
* Sharing and collaboration of data-driven applications.
* Multi-user productivity tools.

==Problems Solved==
* Simplifies the management and sharing of applications.
* Enables easy deployment and operation of UI components.
* Facilitates collaboration and sharing between provider and consumer accounts.

==Benefits==
* Streamlines application management and sharing processes.
* Increases efficiency in deploying and operating UI components.
* Enhances collaboration and productivity among users.

'''Abstract'''
 A data platform for managing an application as a first-class database object. The data object can include User Interface (UI) components. The data application can be shared by a provider account to a plurality of consumer accounts using a share object and based on grant commands. The consumer accounts can deploy and operate the UI component based on the share object.

===SHARING OF UNSTRUCTURED DATA IN STAGES ([[17933761. SHARING OF UNSTRUCTURED DATA IN STAGES simplified abstract (Snowflake Inc.)|17933761]])===


'''Main Inventor'''

Subramanian Muralidhar


'''Brief explanation'''
 The patent application describes systems and methods for sharing unstructured data in stages. Here is a simplified explanation of the abstract:

* The invention involves a method for sharing unstructured data between a data provider and a data consumer.
* A share object is generated by the data provider, which includes information about the data consumer's account and the unstructured data files being shared.
* The share object is configured with access privileges, determining the level of access the data consumer has to the shared data files.
* A notification is then sent to the data consumer's account, informing them about the share object and the shared data files.

Potential applications of this technology:

* Collaborative work environments where multiple users need access to the same unstructured data files.
* Sharing large files or datasets between different accounts or organizations.
* Securely sharing sensitive information with specific individuals or groups.

Problems solved by this technology:

* Simplifies the process of sharing unstructured data by providing a structured and controlled method.
* Ensures that only authorized individuals or groups have access to the shared data files.
* Streamlines collaboration and data sharing workflows.

Benefits of this technology:

* Improved data security and privacy by controlling access to shared data files.
* Enhanced collaboration and productivity by enabling efficient sharing of unstructured data.
* Simplified sharing process reduces the risk of errors or data loss.

'''Abstract'''
 Provided herein are systems and methods for sharing unstructured data in stages. For example, a method includes generating a share object at an account of a data provider. The share object identifies an account of a data consumer and at least one unstructured data file shared with the account of the data consumer. The share object is configured with access privileges to the at least one unstructured data file. A notification of the share object is communicated to the account of the data consumer.

===DATA CLEAN ROOMS USING DEFINED ACCESS IN TRUSTED EXECUTION ENVIRONMENT ([[18060504. DATA CLEAN ROOMS USING DEFINED ACCESS IN TRUSTED EXECUTION ENVIRONMENT simplified abstract (Snowflake Inc.)|18060504]])===


'''Main Inventor'''

Artin Avanes


'''Brief explanation'''
 The abstract of this patent application describes a system where an application is created on a data-provider platform. The application includes APIs that correspond to underlying code blocks. Provider data is shared with the application, and an application instance is installed in a trusted execution environment (TEE). Consumer data is shared with the application instance, and the APIs are invoked to execute the associated code blocks on the TEE. The output is saved to the data-consumer platform.

* The application is created on a data-provider platform.
* APIs are used to correspond to underlying code blocks.
* Provider data is shared with the application.
* An application instance is installed in a trusted execution environment (TEE).
* Consumer data is shared with the application instance.
* APIs are invoked to execute associated code blocks on the TEE.
* The output of the code blocks is saved to the data-consumer platform.

== Potential Applications ==
This technology has potential applications in various fields, including:

* Secure data processing and analysis
* Confidential computing
* Trusted execution environments
* Data privacy and protection

== Problems Solved ==
This technology addresses several problems, such as:

* Ensuring the security and privacy of data during processing
* Protecting sensitive information from unauthorized access
* Enabling secure execution of code blocks in a trusted environment
* Facilitating secure data sharing between data providers and consumers

== Benefits ==
The benefits of this technology include:

* Enhanced data security and privacy
* Confidential computing capabilities
* Secure execution of code blocks in a trusted environment
* Improved trust between data providers and consumers
* Facilitated data sharing while maintaining data confidentiality.

'''Abstract'''
 In an embodiment, an application is created on a data-provider platform. The application includes one or more application programming interfaces (APIs) corresponding to one or more underlying code blocks. Provider data is shared with the application on the data-provider platform. An application instance of the application is installed in a trusted execution environment (TEE). The application instance includes one or more APIs corresponding to the one or more APIs in the application on the data-provider platform. Consumer data is shared with the application instance from a data-consumer platform. One or more of the APIs of the application instance are invoked to execute, on the TEE, respective associated underlying code blocks that are not visible on the TEE. The output of the one or more respective associated underlying code blocks is saved to the data-consumer platform.

===DATA CLEAN ROOMS USING DEFINED ACCESS WITH HOMOMORPHIC ENCRYPTION ([[18217163. DATA CLEAN ROOMS USING DEFINED ACCESS WITH HOMOMORPHIC ENCRYPTION simplified abstract (Snowflake Inc.)|18217163]])===


'''Main Inventor'''

Artin Avanes


'''Brief explanation'''
 The abstract of this patent application describes a data platform that creates an application with APIs in a data-provider account. The platform shares encrypted data between the data-provider and data-consumer accounts, and executes code blocks on this encrypted data. The output of these code blocks is saved within the data-consumer account.

* The data platform creates an application with APIs in a data-provider account.
* Homomorphically encrypted provider data is shared with the application in the data-provider account.
* An application instance of the application is installed in a data-consumer account.
* Homomorphically encrypted consumer data is shared with the application instance in the data-consumer account.
* The data platform invokes APIs of the application instance to execute code blocks.
* The code blocks operate on the shared encrypted provider and consumer data.
* The output of the code blocks is saved within the data-consumer account.

== Potential Applications ==
* Secure data sharing between different accounts or entities.
* Privacy-preserving data analysis and processing.
* Collaborative computing where multiple parties can work on encrypted data.

== Problems Solved ==
* Protecting sensitive data while allowing its use in applications.
* Enabling secure data sharing and processing across different accounts.
* Preserving privacy during data analysis and computation.

== Benefits ==
* Enhanced data security through homomorphic encryption.
* Facilitates secure collaboration and data sharing.
* Enables privacy-preserving computation on encrypted data.

'''Abstract'''
 A data platform creates an application in a data-provider account, where the application includes one or more application programming interfaces (APIs) corresponding to one or more underlying code blocks. The data platform shares homomorphically encrypted provider data with the application in the data-provider account. The data platform installs, in a data-consumer account, an application instance of the application. The data platform shares homomorphically encrypted consumer data with the application instance in the data-consumer account. The data platform invokes one or more of the APIs of the application instance to execute respective associated underlying code blocks, which are not visible to the data-consumer account, and which operate on the shared homomorphically encrypted provider data and the shared homomorphically encrypted consumer data. The data platform saves homomorphically encrypted output of the one or more respective associated underlying code blocks locally within the data-consumer account.

===DATA PLATFORM WITH UNIFIED PRIVILEGES ([[18053956. DATA PLATFORM WITH UNIFIED PRIVILEGES simplified abstract (Snowflake Inc.)|18053956]])===


'''Main Inventor'''

Jeremy Yujui Chen


'''Brief explanation'''
 The abstract describes a data platform that allows users to develop and deploy applications within a secure environment. Here are the key points:

* The data platform enables a first user to access and modify the source code of a user application using an editor.
* The platform also allows the first user to set usage privileges for a second user to use the user application.
* To provide the user application to the second user, the platform deploys it by creating a User Defined Function (UDF) server and an application engine within a secure context.
* The user application is instantiated as an application of the application engine within the secure context.
* The platform ensures that the user application can access the necessary data based on the security policies of the secure context.

Potential applications of this technology:

* Software development platforms that require secure access and deployment of user applications.
* Collaborative coding environments where multiple users can work on the same application while maintaining security.
* Cloud-based platforms for deploying and managing user applications with granular access control.

Problems solved by this technology:

* Ensures that user applications are developed and deployed within a unified security context, reducing the risk of unauthorized access or data breaches.
* Provides a secure and controlled environment for users to collaborate on application development and deployment.
* Simplifies the process of granting usage privileges to different users, ensuring that only authorized individuals can access and use the user application.

Benefits of this technology:

* Enhanced security: The platform ensures that user applications are developed and deployed within a secure context, protecting sensitive data and preventing unauthorized access.
* Improved collaboration: Multiple users can work on the same application, set usage privileges, and deploy it within the secure context, facilitating collaborative development.
* Simplified deployment: The platform automates the deployment process by instantiating the necessary servers and engines, making it easier for users to deploy their applications.
* Granular access control: The platform allows the first user to set usage privileges for the second user, enabling fine-grained control over who can access and use the user application.

'''Abstract'''
 A data platform for developing and deploying a user application within a unified security context. The data platform authorizes a first user to use an editor to access source code of a user application based on security policies of a security context and authorizes the first user to use an application and data manager to set usage privileges for a second user to use the user application based on the security policies of the security context. To provide the user application to the second user, the data platform deploys the user application by instantiating a User Defined Function (UDF) server and an application engine of the UDF server within the security context, instantiating the user application as an application of the application engine within the security context, and authorizing access by the user application to databased on the security policies of the security context.