Compare the Top Distributed Databases for Linux as of October 2026

What are Distributed Databases for Linux?

Distributed databases store data across multiple physical locations, often across different servers or even geographical regions, allowing for high availability and scalability. Unlike traditional databases, distributed databases divide data and workloads among nodes in a network, providing faster access and load balancing. They are designed to be resilient, with redundancy and data replication ensuring that data remains accessible even if some nodes fail. Distributed databases are essential for applications that require quick access to large volumes of data across multiple locations, such as global eCommerce, finance, and social media. By decentralizing data storage, they support high-performance, fault-tolerant operations that scale with an organization’s needs. Compare and read user reviews of the best Distributed Databases for Linux currently available using the table below. This list is updated regularly.

  • 1
    InterSystems IRIS

    InterSystems IRIS

    InterSystems

    InterSystems IRIS is a complete cloud-first data platform that includes a multi-model transactional data management engine, an application development platform, and interoperability engine, and an open analytics platform. It is the next generation of our proven data management software.It includes the capabilities of InterSystems Cache and Ensemble, plus a wealth of exciting new capabilities to make it easy to build and deploy cloud based, analytics-intensive enterprise applications with even greater performance and scalability. InterSystems IRIS provides a set of APIs to operate with transactional persistent data simultaneously: key-value, relational, object, document, multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS includes
  • 2
    Objectivity/DB

    Objectivity/DB

    Objectivity, Inc.

    Objectivity/DB is a massively scalable, high performance, distributed Object Database (ODBMS). It is extremely good at handling complex data, where there are many types of connections between objects and many variants. Objectivity/DB can also serve as a massively scalable, high performance graph database. Its DO query language supports standard data retrieval queries as well as high-performance path-based navigational queries. Objectivity/DB is a distributed database, presenting a Single Logical View of its managed data. Data can be hosted on a single machine or distributed across up to 65,000 machines. Connected items can span machines. Objectivity/DB runs on 32 or 64-bit processors running Windows, Linux, and Mac OS X. APIs include: C++, C#, Java and Python. All platform and language combinations are interoperable. For example, objects stored by a program using C++ on Linux can be read by a C# program on Windows and a Java program on Mac OS X.
    Starting Price: See Pricing Details...
  • 3
    eXtremeDB

    eXtremeDB

    McObject

    How is platform independent eXtremeDB different? - Hybrid data storage. Unlike other IMDS, eXtremeDB can be all-in-memory, all-persistent, or have a mix of in-memory tables and persistent tables - Active Replication Fabric™ is unique to eXtremeDB, offering bidirectional replication, multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more - Row & Columnar Flexibility for Time Series Data supports database designs that combine row-based and column-based layouts, in order to best leverage the CPU cache speed - Embedded and Client/Server. Fast, flexible eXtremeDB is data management wherever you need it, and can be deployed as an embedded database system, and/or as a client/server database system -A hard real-time deterministic option in eXtremeDB/rt Designed for use in resource-constrained, mission-critical embedded systems. Found in everything from routers to satellites to trains to stock markets worldwide
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