Best Embedded Database Systems for Redis

Find and compare the best Embedded Database systems for Redis in 2025

Use the comparison tool below to compare the top Embedded Database systems for Redis on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    ArcadeDB Reviews

    ArcadeDB

    ArcadeDB

    Free
    ArcadeDB allows you to manage complex models without any compromises. Polyglot Persistence is gone. There is no need to have multiple databases. ArcadeDB Multi-Model databases can store graphs and documents, key values, time series, and key values. Each model is native to the database engine so you don't need to worry about translations slowing down your computer. ArcadeDB's engine was developed with Alien Technology. It can crunch millions upon millions of records per second. ArcadeDB's traversing speed does not depend on the size of the database. It doesn't matter if your database contains a few records or a billion. ArcadeDB can be used as an embedded database on a single server. It can scale up by using Kubernetes to connect multiple servers. It is flexible enough to run on any platform that has a small footprint. Your data is protected. Our unbreakable fully transactional engine ensures durability for mission-critical production database databases. ArcadeDB uses the Raft Consensus Algorithm in order to maintain consistency across multiple servers.
  • 2
    Tarantool Reviews
    Companies need to find a way to guarantee the uninterrupted operation of their system, high-speed data processing, and reliable storage. In-memory technology has proven to be a good solution for these problems. Tarantool has helped companies around the world for more than 10 years build smart caches and data marts while saving server capacity. Reduce the cost of credentials storage compared to siloed solution and improve service and security for client applications. Reduce the costs of data management by consolidating a large number disparate systems for storing customer identities. Improve the quality and speed of customer recommendations by analyzing user data and behavior. Improve mobile and web channels by speeding up frontends in order to reduce user exit. IT systems in large organizations are operated within a closed network loop, where data is not protected.
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