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Alternatives · Analytics & Time-series

ClickHouse alternatives (2026)

ClickHouse: The analytics database when Postgres is too slow.

Its Catch: Not a general-purpose database—updates and deletes are expensive.

Below: 6 free or free-tier tools from the same category (analytics and time-series databases), free and open source first, then the closest match by shared tags. Each keeps its own Catch.

  1. 1.DuckDBIn-process OLAP database

    Free / OSS · OSS/MIT · 42.3k GitHub stars

    VerdictLocal analytics that just works.

    CatchNot for OLTP workloads—it is analytics-focused. Single-node limits apply. Less ecosystem than traditional databases.

  2. 2.DuckLakeMIT lakehouse table format on SQL + Parquet — a DuckDB extension

    Free / OSS · OSS/MIT · 3.3k GitHub stars

    VerdictMIT SQL-catalog lakehouse format when DuckDB is your engine and Iceberg’s catalog stack feels heavy — confirm multi-engine support first.

    CatchNeeds a separate catalog database you run and back up (DuckDB file for one writer, Postgres/MySQL for multi-client). Engines outside DuckDB support it far less widely than Iceberg or Delta Lake — check your Spark/Trino/warehouse story before committing. Younger format with a shorter production track record. Vs the duckdb gem: DuckDB is the engine; DuckLake is the table format and catalog layer on top.

  3. 3.QuestDBApache-2.0 low-latency time-series database with SQL

    Free / OSS · Apache-2.0 · 17.4k GitHub stars

    VerdictOne of the fastest open time-series databases — great for market data and telemetry.

    CatchBenchmarks are the vendor's own. Automatic tiering of cold partitions to object storage, replication and other features are in QuestDB Enterprise; in open source you convert partitions to Parquet yourself. It is built for append-heavy time-series, not general OLTP with frequent updates.

  4. 4.TrinoApache-2.0 distributed SQL query engine for data lakes

    Free / OSS · Apache-2.0 · 13.3k GitHub stars

    VerdictThe standard open engine for SQL over a lakehouse — bring your own storage and catalog.

    CatchIt is a query engine, not storage: you still need a catalog and files or databases underneath. Running a coordinator plus workers on the JVM needs memory tuning, and building from source requires Java 25 and Docker. Starburst sells the commercial distribution; plain Trino is fully open.

  5. 5.DatabendApache-2.0 Rust cloud data warehouse on object storage

    Free / OSS · Apache-2.0 · 9.5k GitHub stars

    VerdictA Snowflake-style warehouse you can run yourself — compare with ClickHouse before choosing.

    CatchThe README now positions it as an enterprise warehouse for AI agents, and the recommended start is Databend Cloud (free to start, commercial beyond that); self-hosting a cluster is more work. Smaller ecosystem than ClickHouse or DuckDB. Releases are frequent nightly-style builds, so pin versions.

  6. 6.StarRocksApache-2.0 MPP SQL engine for lakehouse analytics

    Free / OSS · Apache-2.0 · 12.2k GitHub stars

    VerdictA strong choice for customer-facing dashboards on big data — benchmark it on your own queries.

    CatchPerformance claims (3x faster on average) are the project's own. A cluster is frontend and backend nodes to size and operate. It is an analytics engine, not a transactional database. CelerData sells the commercial version.

FAQ

What are the best free alternatives to ClickHouse?
DuckDB, DuckLake, QuestDB, Trino, Databend. All are reviewed on Stack Gems in the same category (analytics and time-series databases); 6 free or open source.
What is the catch with ClickHouse?
Not a general-purpose database—updates and deletes are expensive.
Is there an open-source alternative to ClickHouse?
Yes: DuckDB (OSS/MIT), DuckLake (OSS/MIT), QuestDB (Apache-2.0), Trino (Apache-2.0).

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