SQL that branches

Performance

Fused SIMD execution over copy-on-write columnar data. Single-threaded comparison vs DuckDB v1.4.4 (JDBC in-process) on 10M rows, Intel Core Ultra 7 258V, JVM 25. Median of 10 iterations, 5 warmup:

Stratum wins 35 of 46 queries at 10M rows (single-threaded, median of 10 runs, Intel Core Ultra 7). DuckDB wins on sparse-selectivity filters, high-cardinality hash group-by, and global COUNT(DISTINCT). Full methodology and raw results in the benchmark docs.

Branch anything

st/fork creates an O(1) copy-on-write branch - no data copied, only a pointer to shared chunks. st/sync! persists a branch to storage. st/load restores any named branch. Pass column data as a table map to SQL queries, or register live storage-backed tables in the server with register-live-table!.

(require '[stratum.api :as st]
         '[konserve.file-store :as fs]
         '[clojure.core.async :refer [<!!]])

;; Open storage and load the orders dataset (10M rows)
(def store  (<!! (fs/new-fs-store "/data/stratum")))
(def orders (<!! (st/load store "orders")))

;; Fork in O(1) - structural sharing, zero data copied
(def experiment (st/fork orders))

;; Persist fork as a named branch - shares chunks with main
(<!! (st/sync! experiment store "experiment"))

;; Query both branches via SQL - pass column data as table map
(st/q "SELECT SUM(price * qty) FROM t" {"t" (st/columns orders)})
;; => {:SUM(price * qty) 4821903.40}   ← main branch unchanged

(st/q "SELECT SUM(price * qty) FROM t" {"t" (st/columns experiment)})
;; => {:SUM(price * qty) 4401238.66}   ← experiment branch

;; Time-travel: load any historical branch from storage
(def baseline (<!! (st/load store "orders-baseline")))
(st/q "SELECT COUNT(*) FROM t" {"t" (st/columns baseline)})
;; => {:COUNT(*) 9847233}

Yggdrasil extends branching across your whole stack - fork Datahike, Stratum, and Proximum together for consistent snapshot isolation across SQL, Datalog, and vector search. Yggdrasil → · Dataset API docs →

Why Stratum

Datahike is the system-of-record: Datalog queries, immutable transactions, time travel. Stratum is the SIMD SQL engine for scans and analytics over those same snapshots - fast on group-bys, joins, and window functions where a triple index isn't the right memory layout.

Quick start

# Java 21+, no Clojure needed
java --add-modules jdk.incubator.vector \
     --enable-native-access=ALL-UNNAMED \
     - jar stratum-standalone.jar \
     --index orders:/data/orders.csv

# Or try the built-in demo tables (lineitem, taxi -100K rows each)
java --add-modules jdk.incubator.vector \
     --enable-native-access=ALL-UNNAMED \
     - jar stratum-standalone.jar --demo

# Connect with any PostgreSQL client
psql - h localhost - p 5432 - U stratum

(require '[stratum.api :as st])

;; Query with DSL
(st/q {:from {:price prices :qty quantities}
       :where [[:> :price 100]]
       :group [:region]
       :agg   [[:sum [:* :price :qty]]
               [:count]]})

;; Or with SQL
(st/q "SELECT region, SUM(price * qty), COUNT(*)
       FROM orders WHERE price > 100 GROUP BY region"
      {"orders" {:price prices :qty quantities
                 :region regions}})

How it works

SQL capabilities

• DML - SELECT, INSERT, UPDATE, DELETE, UPSERT (INSERT ON CONFLICT), UPDATE FROM, CREATE TABLE, DROP TABLE
• Aggregates - SUM, COUNT, AVG, MIN, MAX, STDDEV, VARIANCE, CORR, MEDIAN, PERCENTILE_CONT, APPROX_QUANTILE, COUNT(DISTINCT), FILTER clause
• Group-by - any number of columns, string and numeric, with HAVING
• Joins - INNER, LEFT, RIGHT, FULL with multi-column keys
• Window functions - ROW_NUMBER, RANK, DENSE_RANK, NTILE, PERCENT_RANK, CUME_DIST, LAG, LEAD, SUM/COUNT/AVG/MIN/MAX OVER with frame clauses
• Composition - CTEs (WITH), subqueries, IN/EXISTS, UNION/INTERSECT/EXCEPT
• Expressions - CASE WHEN, COALESCE, NULLIF, GREATEST, LEAST, CAST
• Date/time - DATE_TRUNC, EXTRACT, DATE_ADD, DATE_DIFF
• String - LIKE/ILIKE, UPPER/LOWER, LENGTH, SUBSTR
• Files - FROM read_csv('file.csv'), FROM read_parquet('file.parquet')
• Analytics - ANOMALY_SCORE, ANOMALY_PREDICT, ANOMALY_PROBA, ANOMALY_CONFIDENCE (isolation forest via SQL; online rotation for concept drift - docs)
• Other - EXPLAIN, SELECT DISTINCT, IS NULL/IS NOT NULL, LIMIT/OFFSET

Work with us

If you need help getting Stratum into production, we can help with integration, custom development, and support contracts.

Installation

; deps.edn (Clojure CLI)
; check https://clojars.org/org.replikativ/stratum for latest version
{:deps {org.replikativ/stratum {:mvn/version "0.1.114"}}}

; JVM flags required (add to :jvm-opts or alias)
:jvm-opts ["--add-modules=jdk.incubator.vector"
           "--enable-native-access=ALL-UNNAMED"]

;; Leiningen - project.clj
;; [org.replikativ/stratum "0.1.114"]

Requires JDK 21+. Clojure 1.12+. Apache 2.0 license. Latest version on Clojars.