Open-source SingleStore alternatives

ClickHouse is an open-source database management system built to generate analytical reports in real time. Its column-oriented storage makes scans and aggregations over very large tables efficient, which is why it is widely used for event data, logs, metrics and product analytics. It is written in C++ and queried with SQL.

The project's topics describe it as an OLAP, massively parallel and distributed system, and it is used for big data workloads where query latency matters. You can install it on Linux, macOS or FreeBSD, follow a tutorial that sets up a small cluster, or skip installation by trying ClickHouse Cloud, a managed service built by its creators. Releases arrive monthly, with a community call for each one, and there are Slack and Telegram channels for help.

ClickHouse is Apache-2.0 licensed. It is a good fit for analytics engineers and platform teams who need fast aggregations over billions of rows and are comfortable operating a database, or who prefer to hand that operation to the vendor's cloud.

TiDB is a cloud-native, open-source distributed SQL database from PingCAP. The name's Ti stands for titanium, and it is built for high availability, strong consistency and the ability to scale out as data and traffic grow, while staying compatible with MySQL so existing applications and tools can connect with little change.

Distributed transactions use a two-phase commit protocol to keep ACID guarantees even across nodes, through network partitions or node failures. It scales horizontally by adding nodes or vertically by adding resources, without downtime, and its architecture separates compute from storage so each can be adjusted independently. Built-in Raft consensus keeps multiple replicas in sync and handles automated failover. Topics also mention HTAP workloads, analytics and native vector search.

TiDB is written in Go under the Apache-2.0 license. It can be deployed on your own infrastructure or consumed as a managed cloud service, and it suits teams that have outgrown a single MySQL server and want horizontal scale without sharding by hand.

Apache Doris is an open-source analytics database built on a massively parallel processing architecture. It offers fast SQL analytics, acceleration of queries over lakehouse data, and hybrid search spanning structured, text and vector data, and it presents itself as a real-time analytics and search engine suitable for AI agents. It is written in Java.

The README lists use cases that include customer-facing analytics with sub-second interactive queries for external users, data warehousing across business domains, observability for high-throughput logs, events and metrics analyzed with SQL, and AI use where vector, text, JSON and structured search run in one SQL engine. Topics mention lakehouse formats Hudi, Iceberg and Delta Lake and comparisons with warehouses such as BigQuery, Redshift and Snowflake.

Doris is a project of the Apache Software Foundation and Apache-2.0 licensed. You can deploy it on your own clusters, and the website provides release notes, use cases and user stories, with documentation in a large number of languages. It suits data engineering teams that want an open-source, high-concurrency analytical database.

StarRocks is a query engine for analytics that returns answers quickly to multi-dimensional, real-time and ad-hoc queries. It is a Linux Foundation project written in Java, and can be used both on its own tables and over data that sits in a data lake or lakehouse without first moving it.

It uses a vectorized SQL engine that takes advantage of CPU parallelism, supports standard ANSI SQL and the MySQL protocol so existing clients and BI tools can connect, and applies a cost-based optimizer to complex queries. Primary-key tables support upserts and deletes with efficient querying during concurrent updates, and materialized views refresh during data import and are chosen automatically at query time.

Data in Hive, Iceberg, Delta Lake and Hudi tables can be queried in place, and its topics point to star-schema, MPP and distributed-database designs. The software is licensed under Apache-2.0 and can be downloaded and run yourself, with documentation, benchmarks and a demo linked from the README. It suits data teams that want fast dashboards and lakehouse analytics without heavy denormalization.

OceanBase is a distributed relational database developed by Ant Group. It runs on a cluster of commodity servers and uses the Paxos protocol and a distributed architecture to provide high availability and scalability, without depending on a specific hardware architecture.

It is compatible with MySQL, which eases migration from MySQL databases, and supports hybrid transactional and analytical processing, so one engine can serve both OLTP and OLAP workloads. The project now describes itself as a unified, multi-model database for the AI era, with topics that include vector search and full-text search. Cloud-native operation is supported through a Kubernetes operator.

You can try it by deploying a stand-alone instance with an all-in-one package on Linux, starting a Docker container from images on Docker Hub, quay.io or ghcr.io, or running it on Kubernetes with ob-operator. OceanBase is written in C++ and licensed under Apache-2.0, with a developer guide for compiling the observer yourself.

CrateDB is a scalable, distributed SQL database for storing and analyzing very large volumes of data in near real time, including complex queries. It is compatible with PostgreSQL and based on Lucene, and the vendor describes answers in under a second across datasets of millions to billions of rows and many data types, without pre-aggregation.

The product handles many data models in one engine, including time series, document and JSON, vector, full-text, spatial and relational data. Its repository topics mention IoT, industrial IoT, OLAP, analytics and vector databases. The code is written in Java, and the vendor lists solutions for real-time industrial analytics, AI operations and application analytics across industries such as manufacturing and energy.

CrateDB is licensed under Apache-2.0 in its open-source edition. It is available as the OSS build you run yourself, as an enterprise edition and as the managed CrateDB Cloud, with pricing published on the vendor's site. It suits teams building analytics on high-volume machine and event data.