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  2. Hazelcast - Wikipedia

    en.wikipedia.org/wiki/Hazelcast

    In computing, Hazelcast is a unified real-time data platform [3] implemented in Java that combines a fast data store with stream processing. It is also the name of the company that is developing the product. The Hazelcast company is funded by venture capital and headquartered in Palo Alto, California. [4] [5] [6]

  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. Qizx - Wikipedia

    en.wikipedia.org/wiki/Qizx

    The client-server version supports database clustering for both load balancing and data redundancy. Qizx is bundled with a multi-platform GUI client and can also be accessed through a RESTful API that includes embedded online documentation. Qizx includes bindings in Java, Python, C and C# as well as native XPath and XQuery support.

  5. Comparison of distributed file systems - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_distributed...

    1 per TB of storage Coda: C GPL C Yes Yes Replication Volume [5] 1987 GlusterFS: C GPLv3 libglusterfs, FUSE, NFS, SMB, Swift, libgfapi mirror Yes Reed-Solomon [6] Volume [7] 2005 HDFS: Java Apache License 2.0 Java and C client, HTTP, FUSE [8] transparent master failover No Reed-Solomon [9] File [10] 2005 IPFS: Go Apache 2.0 or MIT

  6. Apache Parquet - Wikipedia

    en.wikipedia.org/wiki/Apache_Parquet

    Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.

  7. 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.

  8. Apache Druid - Wikipedia

    en.wikipedia.org/wiki/Apache_Druid

    Druid is designed to quickly ingest massive quantities of event data, and provide low-latency queries on top of the data. [3] The name Druid comes from the shapeshifting Druid class in many role-playing games , to reflect that the architecture of the system can shift to solve different types of data problems.

  9. Zarr (data format) - Wikipedia

    en.wikipedia.org/wiki/Zarr_(data_format)

    Zarr is an open standard for storing large multidimensional array data. It specifies a protocol and data format, and is designed to be "cloud ready" including random access, by dividing data into subsets referred to as chunks. [1] [2] Zarr can be used within many programming languages, including Python, Java, JavaScript, C++, Rust and Julia. [3]