Abstract: The systems and methods described here can reduce the storage space required (memory and/or disk) to store certain types of data, provide efficient (fast) creation, modification and retrieval of such data, and support such data within the framework of a multi-version database. In some embodiments, the systems and methods can store each field of a set of records as a vector of values, e.g., a data vector. A set of records can be represented using a vector hash vector, or “vhash” vector, wherein each element of the vhash vector contains a unique identifier of a data vector, based on a cryptographic hash of the data vector. A header table can store associations between labels and “vhash” vectors that pertain to those labels. Identical data vectors can be re-used between different record sets or vhash vectors needing that vector, thus saving space.

Abstract: The systems and methods described here can reduce the storage space required (memory and/or disk) to store certain types of data, provide efficient (fast) creation, modification and retrieval of such data, and support such data within the framework of a multi-version database. In some embodiments, the systems and methods can store each field of a set of records as a vector of values, e.g., a data vector. A set of records can be represented using a vector hash vector, or “vhash” vector, wherein each element of the vhash vector contains a unique identifier of a data vector, based on a cryptographic hash of the data vector. A header table can store associations between labels and “vhash” vectors that pertain to those labels. Identical data vectors can be re-used between different record sets or vhash vectors needing that vector, thus saving space.

Abstract: Systems and methods for computer memory management by a memory coordinator and a plurality of memory consumers. An urgency and memory quota of each memory consumer is initialized by the memory coordinator, which then adjusts the memory quota of each memory consumer such that the sum of the memory quota of each memory consumer does not exceed a finite amount of computer memory. Each memory consumer adjusts its memory usage in response to the quota input and urgency input from the memory coordinator.

Abstract: Systems and methods for computer memory management by a memory coordinator and a plurality of memory consumers. An urgency and memory quota of each memory consumer is initialized by the memory coordinator, which then adjusts the memory quota of each memory consumer such that the sum of the memory quota of each memory consumer does not exceed a finite amount of computer memory. Each memory consumer adjusts its memory usage in response to the quota input and urgency input from the memory coordinator.

Abstract: The systems and methods described here can reduce the storage space required (memory and/or disk) to store certain types of data, provide efficient (fast) creation, modification and retrieval of such data, and support such data within the framework of a multi-version database. In some embodiments, the systems and methods can store each field of a set of records as a vector of values, e.g., a data vector. A set of records can be represented using a vector hash vector, or “vhash” vector, wherein each element of the vhash vector contains a unique identifier of a data vector, based on a cryptographic hash of the data vector. A header table can store associations between labels and “vhash” vectors that pertain to those labels. Identical data vectors can be re-used between different record sets or vhash vectors needing that vector, thus saving space.

Abstract: The systems and methods described here can reduce the storage space required (memory and/or disk) to store certain types of data, provide efficient (fast) creation, modification and retrieval of such data, and support such data within the framework of a multi-version database. In some embodiments, the systems and methods can store each field of a set of records as a vector of values, e.g., a data vector. A set of records can be represented using a vector hash vector, or “vhash” vector, wherein each element of the vhash vector contains a unique identifier of a data vector, based on a cryptographic hash of the data vector. A header table can store associations between labels and “vhash” vectors that pertain to those labels. Identical data vectors can be re-used between different record sets or vhash vectors needing that vector, thus saving space.

Abstract: The systems and methods described here can reduce the storage space required (memory and/or disk) to store certain types of data, provide efficient (fast) creation, modification and retrieval of such data, and support such data within the framework of a multi-version database. In some embodiments, the systems and methods can store each field of a set of records as a vector of values, e.g., a data vector. A set of records can be represented using a vector hash vector, or “vhash” vector, wherein each element of the vhash vector contains a unique identifier of a data vector, based on a cryptographic hash of the data vector. A header table can store associations between labels and “vhash” vectors that pertain to those labels. Identical data vectors can be re-used between different record sets or vhash vectors needing that vector, thus saving space.

Abstract: A system for calculating analytics uses a relational database to store inputs, calculates results, and stores them in cache. The system also includes an access layer that provides a unified view of the data in server. A dynamic access layer is generated at runtime to run an analytic to provide a flexible framework for creating business logic.

Abstract: A system for calculating analytics uses a relational database to store inputs, calculates results, and stores them in cache. The system also includes an access layer that provides a unified view of the data in server. A dynamic access layer is generated at runtime to run an analytic to provide a flexible framework for creating business logic.

Abstract: A system for calculating analytics uses a relational database to store inputs, calculates results, and stores them in cache. The system also includes an access layer that provides a unified view of the data in server. A dynamic access layer is generated at runtime to run an analytic to provide a flexible framework for creating business logic.