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  2. InfiniteGraph - Wikipedia

    en.wikipedia.org/wiki/InfiniteGraph

    InfiniteGraph is a distributed graph database implemented in Java and C++ and is from a class of NOSQL ("Not Only SQL") database technologies that focus on graph data structures. Developers use InfiniteGraph to find useful and often hidden relationships in highly connected, complex big data sets.

  3. NoSQL - Wikipedia

    en.wikipedia.org/wiki/NoSQL

    Since this non-relational database design does not require a schema, it offers rapid scalability to manage large and typically unstructured data sets. [2] NoSQL systems are also sometimes called "Not only SQL" to emphasize that they may support SQL-like query languages or sit alongside SQL databases in polyglot-persistent architectures. [3] [4]

  4. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    Graph databases portray the data as it is viewed conceptually. This is accomplished by transferring the data into nodes and its relationships into edges. A graph database is a database that is based on graph theory. It consists of a set of objects, which can be a node or an edge.

  5. List of in-memory databases - Wikipedia

    en.wikipedia.org/wiki/List_of_in-memory_databases

    ArangoDB is a transactional native multi-model database supporting two major NoSQL data models (graph and document [1]) with one query language. Written in C++ and optimized for in-memory computing. In addition ArangoDB integrated RocksDB for persistent storage. ArangoDB supports Java, JavaScript, Python, PHP, NodeJS, C++ and Elixir.

  6. Cypher (query language) - Wikipedia

    en.wikipedia.org/wiki/Cypher_(query_language)

    Firstly, the graph model can be a natural fit for data sets that have hierarchical, complex, or even arbitrary structures. Such structures can be easily encoded into the graph model as edges. This can be more convenient than the relational model, which requires the normalization of the data set into a set of tables with fixed row types.

  7. Aerospike (database) - Wikipedia

    en.wikipedia.org/wiki/Aerospike_(database)

    Aerospike Database is a real-time, high performance NoSQL database. Designed for applications that cannot experience any downtime and require high read & write throughput. Aerospike is optimized to run on NVMe SSDs capable of efficiently storing large datasets (Gigabytes to Petabytes). Aerospike can also be deployed as a fully in-memory cache ...

  8. Cosmos DB - Wikipedia

    en.wikipedia.org/wiki/Cosmos_DB

    It is designed to provide high availability, scalability, and low-latency access to data for modern applications. Unlike traditional relational databases, Cosmos DB is a NoSQL (meaning "Not only SQL", rather than "zero SQL") and vector database, [1] which means it can handle unstructured, semi-structured, structured, and vector data types. [2]

  9. Wide-column store - Wikipedia

    en.wikipedia.org/wiki/Wide-column_store

    It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table. A wide-column store can be interpreted as a two-dimensional key–value store. [1] Google's Bigtable is one of the prototypical examples of a wide-column store. [2]