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New: Version 0.1.2 Live

Supercharge Time-Series on Databricks

A toolkit that brings time-series capabilities to the Databricks Data Intelligence Platform — built on Lakebase, native to Unity Catalog.

Databricks delta logo with glowing data-flow streaks
How LakeTS works

Hot Lakebase, cold Unity Catalog — one query surface

Recent rows live in Lakebase for sub-10ms reads. Lakebase CDF streams older data into a Unity Catalog Managed Table for cheap, long-horizon retention.

create_chronotable.sql
-- One call turns any table into a time-partitioned ChronoTable
CREATE TABLE metrics (
  time   TIMESTAMPTZ NOT NULL,
  device TEXT,
  cpu    DOUBLE PRECISION
);

SELECT lakets.create_chronotable(
  'metrics', 'time', '1 day'
);

-- Or: multi-metric table + chunks + indexes in one call
SELECT lakets.create_metric_table(
  'system_metrics',
  tag_columns    := ARRAY['host', 'region', 'env'],
  field_columns  := ARRAY['cpu', 'memory'],
  chunk_interval := '1 day'
);
ChronoTables

From regular table to ChronoTable in one call

LakeTS partitions your table by time, pre-creates future chunks, and adds BRIN indexes for fast time-range scans. The metadata registry wires the table into time_bucket, RollUps, and Lakehouse Sync automatically.

Drop a 30-day-old chunk in milliseconds — no row-by-row DELETE, no manual partition juggling.

Get started
Critical features

Everything you need for time series at scale