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  2. Cosmos DB - Wikipedia

    en.wikipedia.org/wiki/Cosmos_DB

    Changes are persisted by Cosmos DB, which makes it possible to request changes from any point in time since the creation of the container. A "Time to Live" (or TTL) can be specified at the container level to let Cosmos DB automatically delete items after a certain amount of time expressed in seconds. This countdown starts after the last update ...

  3. Trino (SQL query engine) - Wikipedia

    en.wikipedia.org/wiki/Trino_(SQL_query_engine)

    Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...

  4. Document-oriented database - Wikipedia

    en.wikipedia.org/wiki/Document-oriented_database

    The database system supports document store as well as key/value and graph data models with one database core and a unified query language AQL (ArangoDB Query Language). Yes [8] BaseX: BaseX Team BSD License: Java, XQuery: Support for XML, JSON and binary formats; client-/server based architecture; concurrent structural and full-text searches ...

  5. Comparison of data-serialization formats - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    ^ The primary format is binary, but text and JSON formats are available. [8] [9] ^ Means that generic tools/libraries know how to encode, decode, and dereference a reference to another piece of data in the same document. A tool may require the IDL file, but no more. Excludes custom, non-standardized referencing techniques.

  6. JSON - Wikipedia

    en.wikipedia.org/wiki/JSON

    MongoDB uses JSON-like data for its document-oriented database. Some relational databases, such as PostgreSQL and MySQL, have added support for native JSON data types. This allows developers to store JSON data directly in a relational database without having to convert it to another data format.

  7. Nested set model - Wikipedia

    en.wikipedia.org/wiki/Nested_set_model

    Nested Sets is a clever solution – maybe too clever. It also fails to support referential integrity. It’s best used when you need to query a tree more frequently than you need to modify the tree. [9] The model doesn't allow for multiple parent categories. For example, an 'Oak' could be a child of 'Tree-Type', but also 'Wood-Type'.

  8. InfinityDB - Wikipedia

    en.wikipedia.org/wiki/InfinityDB

    InfinityDB is an all-Java embedded database engine and client/server DBMS with an extended java.util.concurrent.ConcurrentNavigableMap interface (a subinterface of java.util.Map) that is deployed in handheld devices, on servers, on workstations, and in distributed settings.

  9. Jaql - Wikipedia

    en.wikipedia.org/wiki/Jaql

    Jaql (pronounced "jackal") is a functional data processing and query language most commonly used for JSON query processing on big data. It started as an open source project at Google [1] but the latest release was on 2010-07-12. IBM [2] took it over as primary data processing language for their Hadoop software package BigInsights.