Compare the Top Document Databases for Cloud as of November 2025 - Page 2

  • 1
    DataStax

    DataStax

    DataStax

    The Open, Multi-Cloud Stack for Modern Data Apps. Built on open-source Apache Cassandra™. Global-scale and 100% uptime without vendor lock-in. Deploy on multi-cloud, on-prem, open-source, and Kubernetes. Elastic and pay-as-you-go for improved TCO. Start building faster with Stargate APIs for NoSQL, real-time, reactive, JSON, REST, and GraphQL. Skip the complexity of multiple OSS projects and APIs that don’t scale. Ideal for commerce, mobile, AI/ML, IoT, microservices, social, gaming, and richly interactive applications that must scale-up and scale-down with demand. Get building modern data applications with Astra, a database-as-a-service powered by Apache Cassandra™. Use REST, GraphQL, JSON with your favorite full-stack framework Richly interactive apps that are elastic and viral-ready from Day 1. Pay-as-you-go Apache Cassandra DBaaS that scales effortlessly and affordably.
  • 2
    Oracle Database
    Oracle database products offer customers cost-optimized and high-performance versions of Oracle Database, the world's leading converged, multi-model database management system, as well as in-memory, NoSQL, and MySQL databases. Oracle Autonomous Database, available on-premises via Oracle Cloud@Customer or in the Oracle Cloud Infrastructure, enables customers to simplify relational database environments and reduce management workloads. Oracle Autonomous Database eliminates the complexity of operating and securing Oracle Database while giving customers the highest levels of performance, scalability, and availability. Oracle Database can be deployed on-premises when customers have data residency and network latency concerns. Customers with applications that are dependent on specific Oracle database versions have complete control over the versions they run and when those versions change.
  • 3
    ArangoDB

    ArangoDB

    ArangoDB

    Natively store data for graph, document and search needs. Utilize feature-rich access with one query language. Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it. Polyglot persistence without the costs. Easily design, scale and adapt your architectures to changing needs and with much less effort. Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets.
  • 4
    Hazelcast

    Hazelcast

    Hazelcast

    In-Memory Computing Platform. The digital world is different. Microseconds matter. That's why the world's largest organizations rely on us to power their most time-sensitive applications at scale. New data-enabled applications can deliver transformative business power – if they meet today’s requirement of immediacy. Hazelcast solutions complement virtually any database to deliver results that are significantly faster than a traditional system of record. Hazelcast’s distributed architecture provides redundancy for continuous cluster up-time and always available data to serve the most demanding applications. Capacity grows elastically with demand, without compromising performance or availability. The fastest in-memory data grid, combined with third-generation high-speed event processing, delivered through the cloud.
  • 5
    OrientDB
    OrientDB is the world’s fastest graph database. Period. An independent benchmark study by IBM and the Tokyo Institute of Technology showed that OrientDB is 10x faster than Neo4j on graph operations among all the workloads. Drive competitive advantage and accelerate innovation with new revenue streams.
  • 6
    Amazon DocumentDB
    Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. As a document database, Amazon DocumentDB makes it easy to store, query, and index JSON data. Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data. Amazon DocumentDB is designed for 99.99% availability and replicates six copies of your data across three AWS Availability Zones (AZs).
  • 7
    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.
  • 8
    Couchbase Capella
    Couchbase Capella is a cloud database platform that optimizes data storage and processing for both JSON-native operational and analytical data. A faster, better DBaaS for transaction, search, AI, and edge applications, with real-time analytics. Start easily with Capella by using SQL to query your JSON data, and get natural language coding assistance from Capella iQ. Capella is a multipurpose database supporting operational and analytic workloads and use cases, including JSON analytics, vector search, and mobile synchronization. It delivers millisecond response at scale, with the best price-performance of any document Database-as-a-Service. Try for free today and be up and running in minutes. Whether you're tackling development, architectural, or deployment challenges, there are many great reasons to future-proof with Capella.
  • 9
    TopK

    TopK

    TopK

    TopK is a serverless, cloud-native, document database built for powering search applications. It features native support for both vector search (vectors are simply another data type) and keyword search (BM25-style) in a single, unified system. With its powerful query expression language, TopK enables you to build reliable search applications (semantic search, RAG, multi-modal, you name it) without juggling multiple databases or services. Our unified retrieval engine will evolve to support document transformation (automatically generate embeddings), query understanding (parse metadata filters from user query), and adaptive ranking (provide more relevant results by sending “relevance feedback” back to TopK) under one unified roof.