ClickHouse vs doris
Side-by-side comparison of features, pricing, ratings, and alternatives.
ClickHouse is an open-source, column-store database management system for analytical and transactional workloads. It allows for fast data processing and analysis, and is designed for use with large amounts of data.
Apache Doris is an open‑source, high‑performance analytical database designed for real‑time reporting and hybrid search workloads. It combines columnar storage with vectorized execution to deliver low‑latency queries on massive data sets. Built for AI‑driven applications, Doris supports both traditional SQL analytics and approximate nearest‑neighbor search, enabling developers to embed fast, searchable analytics directly into intelligent agents and services.
- High performance and scalability
- Supports real-time data processing and analytics
- Column-store architecture for efficient data storage and retrieval
- Open-source and free to use
- Open‑source and free to use
- Sub‑second query latency on massive data sets
- Native support for vector similarity search
- Compatible with existing MySQL tools and drivers
- Steep learning curve for new users
- Limited support for transactional workloads
- May require significant resources for large-scale deployments
- Relatively new ecosystem, fewer third‑party connectors than older warehouses
- Operational complexity for large clusters requires expertise
- Limited built‑in GUI; relies on external BI tools
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The Verdict
AI-generated from listing dataBoth doris and ClickHouse are free, open‑source columnar databases, but doris adds native vector (ANN) search and MySQL compatibility, while ClickHouse offers broader community adoption and higher raw performance.
Key differences
- •doris provides built‑in approximate nearest‑neighbor (vector) search; ClickHouse does not.
- •ClickHouse has a much larger community (48,708 vs 15,744 GitHub stars) and more mature ecosystem.
- •doris integrates with Spark, Flink, Hive and MySQL clients; ClickHouse focuses on Kafka, HDFS, Arrow.
- •ClickHouse is noted for higher performance and scalability; doris emphasizes sub‑second latency with vector queries.
- •Support channels differ: doris relies on mailing list/Slack; ClickHouse offers email and a community forum.
Pricing & value
Both are free and open‑source; value depends on required features (vector search vs raw performance).
Ease of use / learning curve
ClickHouse noted as having a steep learning curve, but doris also requires expertise for large clusters; overall ClickHouse slightly better documentation.
Features & depth
doris adds native ANN vector search and MySQL‑compatible protocol, which ClickHouse lacks.
Integrations & ecosystem
ClickHouse integrates with Kafka, HDFS, Arrow and has a larger GitHub star count, indicating broader ecosystem.
Collaboration
doris provides a community Slack for real‑time collaboration; ClickHouse only lists email and forum.
Scalability
ClickHouse is praised for high performance and horizontal scaling; doris mentions automatic sharding but is newer.
Support
ClickHouse offers email support and a community forum; doris relies on mailing list and GitHub issues only.
Choose ClickHouse if…
Teams prioritizing raw query performance, larger community, and broader data‑pipeline integrations.
Choose doris if…
Enterprises needing built‑in vector similarity search and MySQL compatibility.
Common questions
Can I run vector similarity queries in ClickHouse?
Not specified; ClickHouse does not list ANN or vector search in its features.
Which database has more community resources and third‑party connectors?
ClickHouse, with 48,708 GitHub stars and integrations like Kafka, HDFS, Arrow, versus doris’s 15,744 stars and fewer connectors.
Do both products support real‑time streaming ingestion?
doris supports batch and streaming pipelines; ClickHouse supports real‑time processing but specific streaming ingestion not detailed.