Mongodb, Inc.

Mathias Stearn

Eliot Horowitz

Geert Bosch

David Lenox Storch

Michael Cahill

Keith Bostic

Dan Pasette

Dwight Allen Merriman

Andrew Michalski Schwerin

Eric Andrew Milkie

Cailin Anne Nelson

Cory P Mintz

Charles William Swanson

Akshay Kumar

A system and computer implemented method for execution of aggregation expressions on a distributed non-relational database system is provided. The method comprises the acts of determining, by a computer system, an optimization for execution of an aggregation operation, wherein the aggregation operation includes a plurality of data operations on a distributed non-relational database; modifying, by the computer system, the plurality of data operations to optimize execution; splitting the aggregation operation into a distributed aggregation operation and a merged aggregation operation; instructing each of a plurality of shard servers to perform the distributed aggregation operation; aggregating, at a merging shard server, the results of the distributed aggregation operation from each of the plurality of shard servers; and performing the merged aggregation operation on the aggregated results of the distributed aggregation operation from each of the plurality of shard servers.

Aggregation framework system architecture and method

According to some aspects, a database system is provided. The database system may include at least one processor configured to execute a plurality of system components. The plurality of system components may include an interface component configured to receive a read commit command and provide a result, a snapshot component configured to generate a plurality of snapshots of data stored in a first data storage node of a plurality of data storage nodes and identify a committed snapshot representative of data that has been replicated on a majority of the plurality of data storage nodes, and a command processing component configured to read the committed snapshot responsive to receipt of the read commit command and generate the result.

Method and apparatus for reading and writing committed data

A system is provided that includes a document validation within a non-relational database system that is capable of reviewing documents according to one or more validation rules. The document validator may be incorporated within a non-relational database engine and may perform validation operations when one or more database functions are performed.

System and interfaces for performing document validation in a non-relational database

According to some aspects, a database system comprising a processor configured to execute a plurality of system components is provided. The plurality of system components may include an interface component configured to receive a write commit command and provide a write commit confirmation, a snapshot component configured to generate a plurality of snapshots of data stored in a data storage node of a plurality of data storage nodes and identify a committed snapshot representative of data that has been replicated on a majority of the plurality of data storage nodes, and a command processing component configured to modify a data element based on the write commit command, determine whether the majority of the plurality of storage nodes have replicated the modification using the committed snapshot, and generate the write commit confirmation responsive to a determination that the majority of the plurality of data storage nodes have replicated the modification.

According to one aspect, methods and systems are provided for selectively employing storage engines in a distributed database environment. The methods and systems can include a processor configured to execute a plurality of system components, wherein the system components comprise an operation prediction component configured to determine an expected set of operations to be performed on a portion of the database; a data format selection component configured to select, based on at least one characteristic of the expected set of operations, a data format for the portion of the database; and at least one storage engine for writing the portion of the database in the selected data format.

Distributed database systems and methods with pluggable storage engines

Systems and methods are provided to enable control and placement of data repositories. In some embodiments, the system segments data into zones. A website, for example, may need to segment data according to location. In this example, a zone may be created for North America and another zone may be created for Europe. Data related to operations executed in North America, for example, can be placed in the North America zone and data related to transactions in Europe can be placed in the Europe zone. According to some embodiments, the system may use zones to accommodate a range of deployment scenarios.

Systems and methods for database zone sharding and API integration

According to one embodiment, a translation component is configured to operate on document encoded data to translate the document encoded data into a canonical format comprising a plurality of canonical types that fold together into a byte stream. The translation component is configured to accept any storage format of data (e.g., column store, row store, LSM tree, etc. and/or data from any storage engine, WIREDTIGER, MMAP, AR tree, Radix tree, etc.) and translate that data into a byte stream to enable efficient comparison. When executing searches and using the translated data to provide comparisons there is necessarily a trade-off based on the cost of translating the data and how much the translated data can be leveraged to increase comparison efficiency.

Systems and methods for data conversion and comparison

A durable memory-mapped database system includes a first memory-mapped view of a database, a second memory-mapped view of the database, a journal buffer and a journal. The first memory-mapped view of the database is a protected view and includes copies of a plurality of datafiles from the database. The second memory-mapped view of the database is a write view and includes copies of the plurality of datafiles. The journal buffer is a buffer in random access memory configured to record datafile updates. The journal is configured to periodically receive recorded datafile updates from the journal buffer.

Growing community of inventors

New York, NY, United States of America

Mathias Stearn