Apache Kylin
Open-source distributed OLAP engine originated at eBay China; one of the first Chinese Apache TLPs.
Our Verdict
Classic cube-based OLAP that still wins on query speed, but modern MPP engines reduce its relative appeal.
Pros
- Sub-second queries on petabyte-scale data
- Pre-computed OLAP cubes for BI workloads
- Supports standard BI tools via JDBC/ODBC
- Mature Apache project with eBay heritage
Cons
- Cube maintenance is operationally heavy
- Less flexible than modern MPP engines
- Adoption declining vs Doris, ClickHouse
- Long build times for large cubes
Best for: Enterprises with fixed BI dashboards needing sub-second queries on huge datasets
Not for: Ad-hoc analytics workloads where query patterns change frequently
When to Use Apache Kylin
Good fit if you need
- Pre-computing OLAP cubes on Hadoop/Spark for sub-second BI
- Replacing slow Hive queries with materialized cube queries
- Powering dashboards on multi-billion row data warehouses
- Enabling analysts to query petabyte data interactively
- Building distributed BI on Kylin cubes with JDBC integration
Lock-in Assessment
Low 5/5
Lock-in Score 5/5
Pricing
Price wrong?Apache Kylin Pricing
- Pricing Model
- free
- Free Tier
- Yes
- Entry Price
- —
- Enterprise Available
- No
- Transparency Score
- —
Beta — estimates may differ from actual pricing
1,000
1001K10K100K1M
Estimated Monthly Cost
$25
Estimated Annual Cost
$300
Estimates are approximate and may not reflect current pricing. Always check the official pricing page.
Community Discussion
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