Best Distributed Databases

Compare the Top Distributed Databases as of October 2026

What are Distributed Databases?

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 currently available using the table below. This list is updated regularly.

  • 1
    HarperDB

    HarperDB

    HarperDB

    HarperDB is a distributed systems platform that combines database, caching, application, and streaming functions into a single technology. With it, you can start delivering global-scale back-end services with less effort, higher performance, and lower cost than ever before. Deploy user-programmed applications and pre-built add-ons on top of the data they depend on for a high throughput, ultra-low latency back end. Lightning-fast distributed database delivers orders of magnitude more throughput per second than popular NoSQL alternatives while providing limitless horizontal scale. Native real-time pub/sub communication and data processing via MQTT, WebSocket, and HTTP interfaces. HarperDB delivers powerful data-in-motion capabilities without layering in additional services like Kafka. Focus on features that move your business forward, not fighting complex infrastructure. You can't change the speed of light, but you can put less light between your users and their data.
    Starting Price: Free
  • 2
    IBM Cloudant
    IBM Cloudant® is a distributed database that is optimized for handling heavy workloads that are typical of large, fast-growing web and mobile apps. Available as an SLA-backed, fully managed IBM Cloud™ service, Cloudant elastically scales throughput and storage independently. Instantly deploy an instance, create databases and independently scale throughput capacity and data storage to meet your application requirements. Encrypt all data, with optional user-defined encryption key management through IBM Key Protect, and integrate with IBM Identity and Access Management. Get continuous availability as Cloudant distributes data across availability zones and 6 regions for app performance and disaster recovery requirements. Get continuous availability as Cloudant distributes data across availability zones and 6 regions for app performance and disaster recovery requirements.
  • 3
    CrateDB

    CrateDB

    CrateDB

    The enterprise database for time series, documents, and vectors. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source distributed database running queries in milliseconds, whatever the complexity, volume and velocity of data.
  • 4
    GigaSpaces

    GigaSpaces

    GigaSpaces

    eRAG (enterprise RAG) combines the power of real-time operational data with GPT’s fantastic user experience: Chat spontaneously and get immediate answers grounded in a unique understanding of your operational data. With its sophisticated semantic reasoning capabilities, eRAG ensures you get accurate, consistent answers. It answers complex, cross-system questions instantly, supports decisions with suggestions, challenges, and next steps. eRAG connects your business data with external events, so that you can weigh the effect of new tax legislation or weather disruptions on your operations. eRAG combines all your operational data sources so you can get a full, unified picture of your business, offering measurable revenue and efficiency outcomes. Through a self-serve UI, IT teams can connect SQL-based databases like Oracle, PostgreSQL, SAP and other systems in just a few clicks. And you can get up and running in 2–3 weeks - no data prep needed.
  • 5
    Google Cloud Bigtable
    Google Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads. Fast and performant: Use Cloud Bigtable as the storage engine that grows with you from your first gigabyte to petabyte-scale for low-latency applications as well as high-throughput data processing and analytics. Seamless scaling and replication: Start with a single node per cluster, and seamlessly scale to hundreds of nodes dynamically supporting peak demand. Replication also adds high availability and workload isolation for live serving apps. Simple and integrated: Fully managed service that integrates easily with big data tools like Hadoop, Dataflow, and Dataproc. Plus, support for the open source HBase API standard makes it easy for development teams to get started.
  • 6
    RocksDB

    RocksDB

    RocksDB

    RocksDB uses a log structured database engine, written entirely in C++, for maximum performance. Keys and values are just arbitrarily-sized byte streams. RocksDB is optimized for fast, low latency storage such as flash drives and high-speed disk drives. RocksDB exploits the full potential of high read/write rates offered by flash or RAM. RocksDB provides basic operations such as opening and closing a database, reading and writing to more advanced operations such as merging and compaction filters. RocksDB is adaptable to different workloads. From database storage engines such as MyRocks to application data caching to embedded workloads, RocksDB can be used for a variety of data needs.
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