https://github.com/databricks-solutions/lakets

LakeTS — Time Series Toolkit for Databricks Lakebase. Pure SQL (PL/pgSQL) functions delivering ChronoTables, RollUps, gap-filling, and Lakehouse Sync on a hot (Lakebase) + cold (Delta) tier — no custom extensions.
https://github.com/databricks-solutions/lakets

databricks delta-lake iot lakebase metrics plpgsql postgres postgresql sql timeseries

Last synced: 8 days ago
JSON representation

LakeTS — Time Series Toolkit for Databricks Lakebase. Pure SQL (PL/pgSQL) functions delivering ChronoTables, RollUps, gap-filling, and Lakehouse Sync on a hot (Lakebase) + cold (Delta) tier — no custom extensions.

• Host: GitHub
• URL: https://github.com/databricks-solutions/lakets
• Owner: databricks-solutions
• License: other
• Created: 2026-05-28T08:46:50.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2026-06-15T06:27:14.000Z (12 days ago)
• Last Synced: 2026-06-15T08:17:44.124Z (12 days ago)
• Topics: databricks, delta-lake, iot, lakebase, metrics, plpgsql, postgres, postgresql, sql, timeseries
• Language: PLpgSQL
• Homepage: https://databricks-solutions.github.io/lakets/
• Size: 9.05 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 12
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Codeowners: .github/CODEOWNERS
  • Security: SECURITY.md
  • Notice: NOTICE.md

Awesome Lists containing this project

README

          
# LakeTS — Time-Series Toolkit for Databricks Lakebase

[![CI Security & Quality Checks](https://github.com/databricks-solutions/lakets/actions/workflows/ci.yml/badge.svg?branch=main)](https://github.com/databricks-solutions/lakets/actions/workflows/ci.yml)

[![Release](https://github.com/databricks-solutions/lakets/actions/workflows/release.yml/badge.svg)](https://github.com/databricks-solutions/lakets/actions/workflows/release.yml)

[![Latest release](https://img.shields.io/github/v/release/databricks-solutions/lakets?sort=semver&label=release)](https://github.com/databricks-solutions/lakets/releases/latest)

[![License](https://img.shields.io/badge/license-Databricks_DB_License-blue)](./LICENSE.md)

[![PostgreSQL](https://img.shields.io/badge/postgres-17%2B-336791?logo=postgresql&logoColor=white)](#)

LakeTS turns Databricks Lakebase (managed PostgreSQL 17) into a time-series database:

automatic time-based partitioning, incremental RollUps, a last-value cache, policy-driven

lifecycle tiering, and one-call sync to Unity Catalog via Lakebase CDF. It is pure PL/pgSQL —

no custom extensions required — with optional Databricks jobs for scheduled maintenance.

## Install

```bash

# Single-file install (recommended) — from a published release

curl -LO https://github.com/databricks-solutions/lakets/releases/latest/download/lakets.sql

psql -q -h  -U  -d  -f lakets.sql

# Or from source

git clone https://github.com/databricks-solutions/lakets.git

psql -q -h  -U  -d  -f lakets/sql/99_install.sql

```

## Quick start

```sql

-- Partition a table by time

CREATE TABLE metrics (time TIMESTAMPTZ NOT NULL, device TEXT, cpu FLOAT8);

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

-- Query with time-series functions

SELECT lakets.time_bucket('1 hour'::interval, time) AS hour,

       avg(cpu), lakets.first(cpu, time), lakets.last(cpu, time)

FROM metrics GROUP BY 1 ORDER BY 1;

-- Lifecycle: keep data resident, then drop once it is durable in Unity Catalog

SELECT lakets.add_tiering_policy('metrics', '7 days');

SELECT lakets.add_retention_policy('metrics', '90 days');

-- Mirror to Unity Catalog (Lakebase CDF)

SELECT lakets.enable_sync('metrics');

```

## Documentation

Full documentation is published at **https://databricks-solutions.github.io/lakets/**:

- **[Getting started](https://databricks-solutions.github.io/lakets/guides/getting-started)** — install, create ChronoTables, run your first query.

- **[How it works](https://databricks-solutions.github.io/lakets/guides/how-it-works)** — partitioning, RollUps, tiering, and Lakebase CDF internals.

- **[How-to guides](https://databricks-solutions.github.io/lakets/how-to)** — RollUps, lifecycle, LVC, alerts, bulk ingest, sync to UC, upgrading.

- **[Reference](https://databricks-solutions.github.io/lakets/reference)** — every function, aggregate, trigger, and metadata table.

## Requirements

- Databricks workspace with Lakebase (PostgreSQL 17+)

- For scheduled maintenance jobs: a Databricks serverless runtime with `pip install -r requirements.txt`

## Contributing

PRs to `main` are validated by CI (SQL lint, Python lint, secret scan, unit tests) — see

[`.github/workflows/ci.yml`](./.github/workflows/ci.yml). Licensed under the

[Databricks License](./LICENSE.md).