Stratum – SQL that branches and beats DuckDB on 35/46 1T benchmarks
How Stratum combines a JVM columnar SQL engine, SIMD execution and copy-on-write branches, with benchmarks and implementation trade-offs.
Stratum – SQL that branches and beats DuckDB on 35/46 1T benchmarks launched on March 12, 2026 with 12 votes, #1,060 of 23,380 launches that month and more than 90% of that year's launches.
In plain words
Stratum is a SQL database tool designed for developers who need high-performance data querying. It outperforms DuckDB on 35 out of 46 one-terabyte benchmarks. The tool focuses on branching capabilities and query optimization, making it suitable for teams working with large datasets who require faster execution speeds than existing alternatives. Stratum targets technical users looking for an efficient SQL solution in their development workflows.
written from the facts on this page · September 2026
From the sources
A few years ago I hit a wall I suspect many data engineers know. I had a million-row analytical dataset and I wanted to run an experiment: modify a few pricing assumptions, re-run a set of aggregation queries, compare the results against the original. Simple enough - except in a mutable database, “compare against the original” means either keeping a copy of the data or hoping nothing changed. Neither approach scales. Datahike solves this for entity-level data. Its storage is EAVT-indexed - like Datomic , tuned for entity traversal and point lookups. That’s the right structure for a system-of-record, but not for scanning 10M rows to compute a GROUP BY with SIMD. Stratum explores the columnar…from datahike.io
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