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Lakekeeper
This is Lakekeeper: A secure, fast, and user-friendly Apache Iceberg REST Catalog built with Rust and available under the Apache License.
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Overview
Iceberg delivers the transactional consistency of a data warehouse while letting compute and storage scale independently on a data lake — warehouse guarantees with data-lake scale.
Our Features
01
Centralized & Open Access Control
Define access control once, in the catalog, and enforce it across every compute engine — no rules duplicated per engine. Permissions are fine-grained and inherited down to individual tables and views, in the model you already use (RBAC, ReBAC, or policy-/attribute-based ABAC), powered by open systems like OpenFGA and OPA with best-in-class engine integration such as Trino.
02
Dynamic Catalog Management
Create, configure and remove Warehouses — your catalogs — at runtime through the API, with no static config files and no server restarts. Storage credentials live in a secure secret store (encrypted in Postgres or a HashiCorp Vault-compatible store), so onboarding a new catalog is a single API call.
03
Row & Column-Level Security
Restrict access to specific rows and columns, not just whole tables. Security-DEFINER views — built on Iceberg's referenced-by model and enforced through trusted query engines — let users read only what an authorized view exposes, never the underlying table directly.
04
OpenID Provider Integration
Use your own identity provider for authentication. Lakekeeper never generates (API)-tokens itself. You already have an IdP. Let's use it!
05
Storage Access Management
Lakekeeper secures access to your data for on-premise and cloud deployments using Vended-Credentials and remote signing for S3.
06
Iceberg & Generic Tables
A standards-compliant Apache Iceberg REST catalog — and more. Register non-Iceberg tables (Lance, Delta, Parquet) as first-class, governed objects with the same credential vending and access control, so one catalog governs your whole lakehouse.
07
Soft-delete & Undrop
Soft-delete with time-bounded undrop and drop-protection across tables, views and generic tables. The catalog runs the cleanup itself, so an accidental drop in a shared environment is recoverable — not fatal.
08
Normalized Database Model
Every entity lives in a fully-typed, normalized schema with real referential integrity — no orphaned metadata, ever. That means fast search across tables, users and roles, plus rich statistics served straight from the catalog, with no object-storage scans.
09
Change Events
Lakekeeper can emit change events to Event Queues like Nats or Kafka to keep stakeholders informed.
10
Extensible
See something that's missing? Build it! Lakekeeper is meant to be extended through. And because Lakekeeper is written in Rust, you can use powerful Rust traits to do so.
11
Rust-Native Performance
Built in Rust with no garbage collector — predictable, low memory use and no GC pauses, with fast startup that suits ephemeral and autoscaled deployments.
12
Easy to Use
Single binary executable for all major platforms; no JVM or Python environment required. Native Kubernetes deployments with Helm chart or k8s operator. UI and batteries included.
13
Production-Ready Operations
No local state — scale the catalog horizontally behind a load balancer, with autoscaling included in the Helm chart. Upgrades stay online too: a read-only maintenance mode keeps reads available while database migrations run, so rolling upgrades never take the catalog offline for readers.
14
Automatic Table Maintenance
Keep query performance high and storage costs low with automated table maintenance — available with Lakekeeper Plus.
15
Enterprise Support & Long-Term Support
Run Lakekeeper at the heart of your data platform with confidence: commercial enterprise support for self-hosted and managed deployments, plus hardened Long-Term Support release lines available with Lakekeeper Plus.
Rust Native
Lakekeeper is written in Rust and based on `iceberg-rust`. No unsafe Code - guaranteed!
Checkout The CodeLearn More
New to Lakekeeper? Start with the Getting Started guide, spin up a ready-to-run example, or watch the talks & demos below.
