Abstract: A cloud-based data platform is disclosed, enabling storage-agnostic data management and analytics in a unified environment. The system may integrate a data lake implemented as a hyperscaler object store, a cloud-based database management system (DBMS), elastic compute resources, and analytics engines. Data may be stored in open table formats, such as Apache Parquet, Delta Lake, and Apache Iceberg, supporting ACID transactions, schema evolution, and efficient query processing. Virtual tables may map data stored in the data lake to the DBMS, enabling in-situ query processing via SQL interfaces. The platform may support advanced features, including change data capture (CDC), time travel, and lifecycle management using a SAGA pattern for atomic operations. Security may be ensured through X.509 certificates, web tokens, and role-based access controls. Elastic compute resources, such as Apache Spark, facilitate large-scale data transformations and analytics.

Abstract: The present invention relates to an improved database system architecture designed for generating and managing heterogeneous graphs. The system utilizes a document store in conjunction with a persistent adjacency index to enhance flexibility, adaptability, and transactional visibility during the generation and modification of complex graph structures. Data stored in the document store utilizes a flexible schema for storing data which improves the efficiency in both storing and retrieving data from the document store during graph-related processing tasks.

Abstract: A method, a system, and a computer program product for generating a pageable hash index for a document store. A hash map index for data stored on disk using a document array is generated. The hash map index includes a plurality of hash values with each hash value identifying a document stored at a predetermined location in the document array. A transaction for executing using a first document stored in the document array is received. Using the generated hash map index, a location of the first document stored in the document array is identified. At least a portion of a first hash value of the hash map index corresponding to the first document is loaded into a memory location without loading the remaining hashes of the hash map index. Based on the loaded portion of the first hash value, the received transaction is executed.

Abstract: A method may include receiving a query including at least one unnest operation to unnest a plurality of elements from one or more JavaScript Object Notation (JSON) arrays. The at least one unnest operation may unnest the plurality of elements by generating a table in which each row of the table is populated by one of the plurality of elements. An execution plan may be generated to include a pre-filter operation to filter, prior to the at least one unnest operation, the plurality of elements included in the one or more JSON arrays. For example, the pre-filter operation may be performed by iterating through the elements from the one or more JSON arrays to identify one or more elements satisfying a predicate included in a where clause of the query. The query may be executed in accordance with the execution plan. Related systems and computer program products are also provided.

Abstract: A method may include generating, based at least on a schema configuration of one or more document stores, a plurality of data in a JavaScript Object Notation (JSON) format for storage at the document stores. One or more queries may be generated to match the plurality of data stored at the document stores. The one or more queries may be distributed for execution at the document stores by a scalable quantity of concurrently operating worker nodes. One or more performance metrics for the execution of the one or more queries at the one or more document stores may be generated. Performance improvements at the document stores may be applied based on the performance metrics. Related systems and computer program products are also provided.

Abstract: The present invention relates to an improved database system architecture designed for generating and managing heterogeneous graphs. The system utilizes a document store in conjunction with a persistent adjacency index to enhance flexibility, adaptability, and transactional visibility during the generation and modification of complex graph structures. Data stored in the document store utilizes a flexible schema for storing data which improves the efficiency in both storing and retrieving data from the document store during graph-related processing tasks.

Abstract: A method, a system, and a computer program product for generating a pageable hash index for a document store. A hash map index for data stored on disk using a document array is generated. The hash map index includes a plurality of hash values with each hash value identifying a document stored at a predetermined location in the document array. A transaction for executing using a first document stored in the document array is received. Using the generated hash map index, a location of the first document stored in the document array is identified. At least a portion of a first hash value of the hash map index corresponding to the first document is loaded into a memory location without loading the remaining hashes of the hash map index. Based on the loaded portion of the first hash value, the received transaction is executed.

Abstract: According to some embodiments, a central cloud-based repository of data may contain consolidated facts about enterprise applications. A computer processor of a discovery engine may execute discovery in a local application process and, based on the executed discovery, automatically create a generic structured set of facts from locally accessible data. The discovery engine may then store the generic structured set of facts in the central cloud-based data repository using a standard format (e.g., JSON). The central cloud-based data repository may, for example, store facts from different application instances and/or facts from different applications. According to some embodiments, a user generated query is created in a query language (e.g., SQL) and executed on the central cloud-based repository of data to automatically create an answer. Moreover, an automated ML agent may, in some embodiments, evaluate information in the central cloud-based repository of data.

Abstract: A method may include parsing, using a JavaScript Object Notation (JSON) parser implemented on a field programmable gate array (FPGA), a JSON document. The parsing includes dividing an input string comprising the JSON document into one or more data blocks and annotating the characters included in each data block a bitmap for each data block. String characters included in the data blocks may be identified, based on the bitmap associated with each data block, for writing to a string array. Numeric characters included in the data blocks may be transformed, based on the bitmap associated with each data block, into integers value for writing to an integer array or float values for writing to a float array. A tape including a binary representation of the JSON document may be generated based on the bitmap associated with each data block. Related systems and computer program products are also provided.

Abstract: A method, a system, and a computer program product for generating a pageable hash index for a document store. A hash map index for data stored on disk using a document array is generated. The hash map index includes a plurality of hash values with each hash value identifying a document stored at a predetermined location in the document array. A transaction for executing using a first document stored in the document array is received. Using the generated hash map index, a location of the first document stored in the document array is identified. At least a portion of a first hash value of the hash map index corresponding to the first document is loaded into a memory location without loading the remaining hashes of the hash map index. Based on the loaded portion of the first hash value, the received transaction is executed.

Abstract: According to some embodiments, a central cloud-based repository of data may contain consolidated facts about enterprise applications. A computer processor of a discovery engine may execute discovery in a local application process and, based on the executed discovery, automatically create a generic structured set of facts from locally accessible data. The discovery engine may then store the generic structured set of facts in the central cloud-based data repository using a standard format (e.g., JSON). The central cloud-based data repository may, for example, store facts from different application instances and/or facts from different applications. According to some embodiments, a user generated query is created in a query language (e.g., SQL) and executed on the central cloud-based repository of data to automatically create an answer. Moreover, an automated ML agent may, in some embodiments, evaluate information in the central cloud-based repository of data.

Abstract: A method, a system, and a computer program product for generating a pageable hash index for a document store. A hash map index for data stored on disk using a document array is generated. The hash map index includes a plurality of hash values with each hash value identifying a document stored at a predetermined location in the document array. A transaction for executing using a first document stored in the document array is received. Using the generated hash map index, a location of the first document stored in the document array is identified. At least a portion of a first hash value of the hash map index corresponding to the first document is loaded into a memory location without loading the remaining hashes of the hash map index. Based on the loaded portion of the first hash value, the received transaction is executed.

Abstract: A method, a system, and a computer program product for providing a compression service, such as a Compression as a Service (Caas). In some implementations, there is provided a method including receiving, at a compression service, metric information regarding one or more columns of a database server; in response to receiving the metric information, processing, by the compression service, the metric information to identify at least one column as a candidate for compression by the compression service; in response to identifying the at least one column, compressing by the compression service, the at least one column, wherein the compression service uses a hardware accelerator to execution a compression algorithm that compresses the at least one column; and notifying, by the compression service, the database server of the at least one column compressed by the compression service. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: A method for graph processing in a scalable graph processing framework may include applying a two-dimensional partitioning scheme to partition a graph. One or more partitions of the graph may be distributed to each graph core such that each graph core executes a graph processing algorithm on one or more partitions of the graph. The executing of the graph processing algorithm may include the graph cores exchanging vertex labels via a crossbar interconnecting the plurality of graph cores. Each graph core in the scalable graph processing framework may be coupled with a single memory channel upon which the partitions of the graph are distributed. The graph cores may synthesized on a field programmable gate array (FPGA) based on one or more user defined functions (UDFs). Related systems and computer program products are also provided.

Abstract: A method, a system, and a computer program product for providing a compression service, such as a Compression as a Service (Caas). In some implementations, there is provided a method including receiving, at a compression service, metric information regarding one or more columns of a database server; in response to receiving the metric information, processing, by the compression service, the metric information to identify at least one column as a candidate for compression by the compression service; in response to identifying the at least one column, compressing by the compression service, the at least one column, wherein the compression service uses a hardware accelerator to execution a compression algorithm that compresses the at least one column; and notifying, by the compression service, the database server of the at least one column compressed by the compression service. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: A method may include receiving a query including at least one unnest operation to unnest a plurality of elements from one or more JavaScript Object Notation (JSON) arrays. The at least one unnest operation may unnest the plurality of elements by generating a table in which each row of the table is populated by one of the plurality of elements. An execution plan may be generated to include a pre-filter operation to filter, prior to the at least one unnest operation, the plurality of elements included in the one or more JSON arrays. For example, the pre-filter operation may be performed by iterating through the elements from the one or more JSON arrays to identify one or more elements satisfying a predicate included in a where clause of the query. The query may be executed in accordance with the execution plan. Related systems and computer program products are also provided.

Abstract: A method may include parsing, using a JavaScript Object Notation (JSON) parser implemented on a field programmable gate array (FPGA), a JSON document. The parsing includes dividing an input string comprising the JSON document into one or more data blocks and annotating the characters included in each data block a bitmap for each data block. String characters included in the data blocks may be identified, based on the bitmap associated with each data block, for writing to a string array. Numeric characters included in the data blocks may be transformed, based on the bitmap associated with each data block, into integers value for writing to an integer array or float values for writing to a float array. A tape including a binary representation of the JSON document may be generated based on the bitmap associated with each data block. Related systems and computer program products are also provided.

Abstract: A method may include generating, based at least on a schema configuration of one or more document stores, a plurality of data in a JavaScript Object Notation (JSON) format for storage at the document stores. One or more queries may be generated to match the plurality of data stored at the document stores. The one or more queries may be distributed for execution at the document stores by a scalable quantity of concurrently operating worker nodes. One or more performance metrics for the execution of the one or more queries at the one or more document stores may be generated. Performance improvements at the document stores may be applied based on the performance metrics. Related systems and computer program products are also provided.

Abstract: A method for graph processing in a scalable graph processing framework may include applying a two-dimensional partitioning scheme to partition a graph. One or more partitions of the graph may be distributed to each graph core such that each graph core executes a graph processing algorithm on one or more partitions of the graph. The executing of the graph processing algorithm may include the graph cores exchanging vertex labels via a crossbar interconnecting the plurality of graph cores. Each graph core in the scalable graph processing framework may be coupled with a single memory channel upon which the partitions of the graph are distributed. The graph cores may synthesized on a field programmable gate array (FPGA) based on one or more user defined functions (UDFs). Related systems and computer program products are also provided.

Abstract: Methods and systems may be associated with application integration in a multi-cloud computing environment. A modeling platform may determine a pattern composition for an integration process associated with a business application. A cost-aware platform may transform a decomposed version of the pattern composition, including a plurality of integration pattern contract graphs, into a multi-cloud cost problem optimization representation. An initial solution to the cost problem representation may be calculated using a modified first fit decreasing bin packing or similar algorithm to determine a configuration of multi-cloud containers and integration pattern contract graph container assignments. The system may then iteratively and locally improve the solution to by applying feasible transformations to create variant container configurations and integration pattern contract graph container assignments that are evaluated based on multi-cloud costs (keeping the user in-the-loop).