Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Techniques to store graph information in a database are disclosed. In various embodiments, each node in a graph may be modeled as a micro b-tree. Node identity, attribute, edge, and edge attribute data may be stored in one or more pages modeled on page formats typically used to store index data for a relational database index. Data associated with a plurality of nodes and edges, each of said edges representing a relationship between two or more of said nodes, may be received. For each node, one or more pages of data may be created, each corresponding to a prescribed page size associated with a storage device in which said one or more pages are to be stored, and each page having a data structure that includes a variable-sized set of fixed length data slots and a variable-sized variable length data region.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Techniques to manage virtual memory are disclosed. In various embodiments, a time domain page access signal of a page is transformed to a frequency domain to obtain an access frequency. The access frequency is used to manage storage of the page in a page cache in memory. The access frequency may be used to evict the page from the page cache or, in some embodiments, to predictively load the page into the page cache.

Abstract: Techniques to provide and deploy a business process are disclosed. A business process source filed stored in a memory is received. The business process source file, as stored in memory, is provided as an input to an in-memory compiler. A business process class file stored in the memory is received as output from the in-memory compiler. The business process class file, as stored in memory, is provided to a business process engine class loader.

Abstract: Techniques to store graph information in a database are disclosed. In various embodiments, each node in a graph may be modeled as a micro b-tree. Node identity, attribute, edge, and edge attribute data may be stored in one or more pages modeled on page formats typically used to store index data for a relational database index. Data associated with a plurality of nodes and edges, each of said edges representing a relationship between two or more of said nodes, may be received.

Abstract: Techniques to store graph information in a database are disclosed. In various embodiments, each node in a graph may be modeled as a micro b-tree. Node identity, attribute, edge, and edge attribute data may be stored in one or more pages modeled on page formats typically used to store index data for a relational database index. Data associated with a plurality of nodes and edges, each of said edges representing a relationship between two or more of said nodes, may be received. For each node, one or more pages of data may be created, each corresponding to a prescribed page size associated with a storage device in which said one or more pages are to be stored, and each page having a data structure that includes a variable-sized set of fixed length data slots and a variable-sized variable length data region.

Abstract: Techniques to provide and deploy a business process are disclosed. A business process source filed stored in a memory is received. The business process source file, as stored in memory, is provided as an input to an in-memory compiler. A business process class file stored in the memory is received as output from the in-memory compiler. The business process class file, as stored in memory, is provided to a business process engine class loader.

Abstract: Techniques to provide and deploy a business process are disclosed. A business process source filed stored in a memory is received. The business process source file, as stored in memory, is provided as an input to an in-memory compiler. A business process class file stored in the memory is received as output from the in-memory compiler. The business process class file, as stored in memory, is provided to a business process engine class loader.

Abstract: Techniques to store graph information in a database are disclosed. In various embodiments, each node in a graph may be modeled as a micro b-tree. Node identity, attribute, edge, and edge attribute data may be stored in one or more pages modeled on page formats typically used to store index data for a relational database index. Data associated with a plurality of nodes and edges, each of said edges representing a relationship between two or more of said nodes, may be received.

Abstract: Techniques to provide and deploy a business process are disclosed. A business process source filed stored in a memory is received. The business process source file, as stored in memory, is provided as an input to an in-memory compiler. A business process class file stored in the memory is received as output from the in-memory compiler. The business process class file, as stored in memory, is provided to a business process engine class loader.

Abstract: Techniques to provide and deploy a business process are disclosed. A business process source filed stored in a memory is received. The business process source file, as stored in memory, is provided as an input to an in-memory compiler. A business process class file stored in the memory is received as output from the in-memory compiler. The business process class file, as stored in memory, is provided to a business process engine class loader.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.

Abstract: Described are systems and methods relating to database query optimization and query cost estimation. The approach is described in the context of searching balanced and semi-balanced tree indexes such as B-trees, B+ trees, and R-B trees. The described approach may be used for both simple and composite queries, and the described approach may be used for relational queries, i.e., where a variable is less than or greater than a certain value and the database is being used to find the set of records that satisfy the relation. Further, the described approach may be used for generalized N-ary tree queries and cost estimations.

Abstract: Controlling client side application congestion at least in part by using one or more heuristics to predict at a data producer node, such as a server, how much time an application at a data consumer node, such as a client, will require to process a unit of data is disclosed. In various embodiments, a predicted client side processing time associated with a unit of data to be sent to a client is determined. The predicted client side processing time associated with the unit of data is used to determine a time to send a data transmission to the client.

Abstract: Policy-based storage and retrieval combined with a distribution algorithm results in automatic and even distribution of policy-based storage structures across a set of nodes and dynamic, automated homing or ownership of policy-based storage structures. Large numbers of policy-based storage structures may be distributed without manual administration, allowing for rapid creation and destruction of storage structures. The overall load may be distributed and balanced across the server pool. Multiple entries having the same key value in a database- or table-like structure allow for distribution of policy-based storage and retrieval by key value and for queue semantics to be utilized for microqueues in the large database- or table-like structure.