TiKV is a highly scalable, low latency, and easy to use
key-value database.
TiKV is a highly scalable, low latency, and easy to use key-value database.

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TiKV provides both raw and ACID-compliant transactional key-value API, which is widely used in online serving services, such as the metadata storage system for object storage service, the storage system for recommendation systems, the online feature store, etc.

TiKV is also widely used as the storage layer for database management systems, for example:
  • TiDB: An open-source MySQL compatible NewSQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads.
  • Zetta: An open-source NoSQL database that supports Transaction and Cloud Spanner like API.
  • Tidis: a Distributed NoSQL database, providing a Redis protocol API (string, list, hash, set, sorted set), written in Go.
  • Titan: A distributed implementation of Redis compatible layer based on TiKV.
  • JuiceFS: An open-source POSIX file system that is based on TiKV and S3.
tikv architecture

Why TiKV

Low and stable latency

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RawKV’s average response time less than 1 ms (P99=10 ms).

High scalability

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With the Placement Driver and carefully designed Raft groups, TiKV excels in horizontal scalability and can easily scale to 100+ terabytes of data. Scale-out your TiKV cluster to fit the data size growth without any impact on the application.

Easy to use

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Run a single command to deploy a TiKV cluster with everything you need for production environments. Easily scale out or scale in the cluster with TiUP or TiKV operator.

Easy to maintain

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TiKV is based on the design of Google Spanner and HBase, but simpler to manage without dependencies on any distributed file system.

Consistent distributed transactions

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Similar to Google’s Spanner, TiKV (TxnKV mode) supports externally consistent distributed transactions.

Adjustable consistency

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In RawKV and TxnKV modes, you can customize the balance between consistency and performance.

Who are using TiKV

Case Studies

TiKV is a Cloud Native Computing Foundation graduate project