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Lakekeeper Catalog for Apache Iceberg

License Unittests Spark Integration Pyiceberg Integration Trino Integration Starrocks Integration Artifact Hub Docker on quay Helm Chart Discord

This is Lakekeeper: A Rust-native implementation of the Apache Iceberg REST Catalog specification based on apache/iceberg-rust.

If you have questions, feature requests or just want a chat, we are hanging around in Discord!

Next Steps

The catalog is evolving quickly. Especially internal rust APIs are not stable and subject to change. External REST APIs are kept as stable as possible, especially the /catalog API is stable as of today.

  • Release 0.5.0: Our biggest release yet is coming early November. It includes Fine Grained Access Control, a first simple UI and much more.
  • Release 0.6.0: With Release 0.6.0 we focus on stabilizing some of our most recent features and significantly improve our Docs. Docusaurus is coming!

Quickstart

A Docker Container is available on quay.io. We have prepared a self-contained docker-compose file to demonstrate the usage of spark with our catalog:

git clone https://github.com/lakekeeper/lakekeeper.git
cd lakekeeper/examples/self-contained
docker compose up

Then open your browser and head to localhost:8888.

For more information on deployment, please check the User Guide.

Scope and Features

The Iceberg Catalog REST interface has become the standard for catalogs in open Lakehouses. It natively enables multi-table commits, server-side deconflicting and much more. It is figuratively the (TIP) of the Iceberg.

We have started this implementation because we were missing customizability, support for on-premise deployments and other features that are important for us in existing Iceberg Catalogs. Please find following some of our focuses with this implementation:

  • Customizable: Our implementation is meant to be extended. We expose the Database implementation, Secrets, Authorization, EventPublishing and ContractValidation as interfaces (Traits). This allows you to tap into any Access management system of your company or stream change events to any system you like - simply by implementing a handful methods. Please find more details in the Customization Guide.
  • Change Events: Built-in support to emit change events (CloudEvents), which enables you to react to any change that happen to your tables.
  • Change Approval: Changes can also be prohibited by external systems. This can be used to prohibit changes to tables that would invalidate Data Contracts, Quality SLOs etc. Simply integrate with your own change approval via our ContractVerification trait.
  • Multi-Tenant capable: A single deployment of our catalog can serve multiple projects - all with a single entrypoint. All Iceberg and Warehouse configurations are completely separated between Warehouses.
  • Written in Rust: Single 30Mb all-in-one binary - no JVM or Python env required.
  • Storage Access Management: Built-in S3-Signing that enables support for self-hosted as well as AWS S3 WITHOUT sharing S3 credentials with clients. We are also working on vended-credentials!
  • Well-Tested: Integration-tested with spark, pyiceberg, trino and starrocks.
  • High Available & Horizontally Scalable: There is no local state - the catalog can be scaled horizontally and updated without downtimes.
  • Openid provider integration: Use your own identity provider to secure access to the APIs, just set LAKEKEEPER__OPENID_PROVIDER_URI and you are good to go.
  • Fine Grained Access (FGA) (Coming soon): Simple Role-Based access control is not enough for many rapidly evolving Data & Analytics initiatives. We are leveraging OpenFGA based on googles Zanzibar-Paper to implement authorization. If your company already has a different system in place, you can integrate with it by implementing a handful of methods in the AuthZHandler trait.

Please find following an overview of currently supported features. Please also check the Issues if you are missing something.

Status

Supported Operations - Iceberg-Rest

Operation Status Description
Namespace done All operations implemented
Table done All operations implemented - additional integration tests in development
Views done Remove unused files and log entries
Metrics open Endpoint is available but doesn't store the metrics

Storage Profile Support

Storage Status Comment
S3 - AWS semi-done vended-credentials & remote-signing, assume role missing
S3 - Custom done vended-credentials & remote-signing, tested against minio
Azure ADLS Gen2 done
Azure Blob open
Microsoft OneLake open
Google Cloud Storage done

Details on how to configure the storage profiles can be found in the Storage Guide.

Supported Catalog Backends

Backend Status Comment
Postgres done
MongoDB open

Supported Secret Stores

Backend Status Comment
Postgres done
kv2 (hcp-vault) done userpass auth

Supported Event Stores

Backend Status Comment
Nats done
Kafka open

Supported Operations - Management API

Operation Status Description
Warehouse Management done Create / Update / Delete a Warehouse
AuthZ open Manage access to warehouses, namespaces and tables
More to come! open

Auth(N/Z) Handlers

Operation Status Description
OIDC (AuthN) done Secure access to the catalog via OIDC
Custom (AuthZ) done If you are willing to implement a single rust Trait, the AuthZHandler can be implement to connect to your system
OpenFGA (AuthZ) open Internal Authorization management

Multiple Projects / Multi-Tenancy

Lakekeeper can host multiple independent projects that each host multiple warehouses. The overall structure looks like this:

<project-1-uuid>/
├─ foo-warehouse
├─ bar-warehouse
<project-2-uuid>/
├─ foo-warehouse
├─ bas-warehouse

Each Project in Lakekeeper corresponds to a distinct Application Object within your IdP, enabling genuine Multi-Tenancy. A single instance of Lakekeeper can host multiple Projects, ensuring separation at all levels, including Authentication. Our Multi-Tenancy definition is broader than most catalogs. While other catalogs may consider hosting multiple warehouses under a single IdP Application as Multi-Tenancy, a single Lakekeeper Project can achieve that and more.

As this additional layer isn't necessary for most deployments, the LAKEKEEPER__ENABLE_DEFAULT_PROJECT configuration option is set to true by default. This setting effectively disables multi-tenancy by defaulting to a project with the NIL UUID ("00000000-0000-0000-0000-000000000000") as the project-id.

To enable multi-project setups, simply set LAKEKEEPER__ENABLE_DEFAULT_PROJECT to false. Multi-project setups require additional configuration to include project-ids in HTTP headers and separate authentication audiences. This documentation does not cover these steps yet. Of course, hosting multiple warehouses within a single Lakekeeper Project is also possible.

Undrop Tables

When a table or view is dropped, it is not immediately deleted from the catalog. Instead, it is marked as dropped and a job for its cleanup is scheduled. The table, including its data if purgeRequested=True, is then deleted after the configured expiration delay has passed. This will allow for a recovery of tables that have been dropped by accident.

Undrop of a table is only possible if soft-deletes are enabled for a Warehouse.

Configuration

The basic setup of the Catalog is configured via environment variables. As this catalog supports a multi-tenant setup, each catalog ("warehouse") also comes with its own configuration options including its Storage Configuration. The documentation of the Management-API for warehouses is hosted at the unprotected /swagger-ui endpoint.

Following options are global and apply to all warehouses:

General

Previous to Lakekeeper Version 0.5.0 please prefix all environment variables with ICEBERG_REST__ instead of LAKEKEEPER__.

Variable Example Description
LAKEKEEPER__BASE_URI https://example.com:8080 Base URL where the catalog is externally reachable. Default: https://localhost:8080
LAKEKEEPER__ENABLE_DEFAULT_PROJECT true If true, the NIL Project ID ("00000000-0000-0000-0000-000000000000") is used as a default if the user does not specify a project when connecting. This option is enabled by default, which we recommend for all single-project (single-tenant) setups. Default: true.
LAKEKEEPER__RESERVED_NAMESPACES system,examples Reserved Namespaces that cannot be created via the REST interface
LAKEKEEPER__METRICS_PORT 9000 Port where the metrics endpoint is reachable. Default: 9000
LAKEKEEPER__LISTEN_PORT 8080 Port the server listens on. Default: 8080
LAKEKEEPER__SECRET_BACKEND postgres The secret backend to use. If kv2 is chosen, you need to provide additional parameters found under Default: postgres, one-of: [postgres, kv2]

Self-signed certificates in dependencies (e.g. minio)

You may be running Lakekeeper in your own environment which uses self-signed certificates for e.g. minio. Lakekeeper is built with reqwest's rustls-tls-native-roots feature activated, this means SSL_CERT_FILE and SSL_CERT_DIR are respected. If both are not set, the system's default CA store is used. If you want to use a custom CA store, set SSL_CERT_FILE to the path of the CA file or SSL_CERT_DIR to the path of the CA directory. The certificate used by the server cannot be a CA. It needs to be an end entity certificate, else you may run into CaUsedAsEndEntity errors.

Task queues

Currently, the catalog uses two task queues, one to ultimately delete soft-deleted tabulars and another to purge tabulars which have been deleted with the purgeRequested=True query parameter. The task queues are configured as follows:

Variable Example Description
LAKEKEEPER__QUEUE_CONFIG__MAX_RETRIES 5 Number of retries before a task is considered failed Default: 5
LAKEKEEPER__QUEUE_CONFIG__MAX_AGE 3600 Amount of seconds before a task is considered stale and could be picked up by another worker. Default: 3600
LAKEKEEPER__QUEUE_CONFIG__POLL_INTERVAL 10 Amount of seconds between polling for new tasks. Default: 10

The queues are currently implemented using the sqlx Postgres backend. If you want to use a different backend, you need to implement the TaskQueue trait.

Postgres

Configuration parameters if Postgres is used as a backend, you may either provide connection strings or use the PG_* environment variables, connection strings take precedence:

Variable Example Description
LAKEKEEPER__PG_DATABASE_URL_READ postgres://postgres:password@localhost:5432/iceberg Postgres Database connection string used for reading
LAKEKEEPER__PG_DATABASE_URL_WRITE postgres://postgres:password@localhost:5432/iceberg Postgres Database connection string used for writing.
LAKEKEEPER__PG_ENCRYPTION_KEY <This is unsafe, please set a proper key> If LAKEKEEPER__SECRET_BACKEND=postgres, this key is used to encrypt secrets. It is required to change this for production deployments.
LAKEKEEPER__PG_READ_POOL_CONNECTIONS 10 Number of connections in the read pool
LAKEKEEPER__PG_WRITE_POOL_CONNECTIONS 5 Number of connections in the write pool
LAKEKEEPER__PG_HOST_R localhost Hostname for read operations
LAKEKEEPER__PG_HOST_W localhost Hostname for write operations
LAKEKEEPER__PG_PORT 5432 Port number
LAKEKEEPER__PG_USER postgres Username for authentication
LAKEKEEPER__PG_PASSWORD password Password for authentication
LAKEKEEPER__PG_DATABASE iceberg Database name
LAKEKEEPER__PG_SSL_MODE require SSL mode (disable, allow, prefer, require)
LAKEKEEPER__PG_SSL_ROOT_CERT /path/to/root/cert Path to SSL root certificate
LAKEKEEPER__PG_ENABLE_STATEMENT_LOGGING true Enable SQL statement logging
LAKEKEEPER__PG_TEST_BEFORE_ACQUIRE true Test connections before acquiring from the pool
LAKEKEEPER__PG_CONNECTION_MAX_LIFETIME 1800 Maximum lifetime of connections in seconds

KV2 (HCP Vault)

Configuration parameters if a KV2 compatible storage is used as a backend. Currently, we only support the userpass authentication method. You may provide the envs as single values like LAKEKEEPER__KV2__URL=http://vault.local etc. or as a compound value like: LAKEKEEPER__KV2='{url="http://localhost:1234", user="test", password="test", secret_mount="secret"}'

Variable Example Description
LAKEKEEPER__KV2__URL https://vault.local URL of the KV2 backend
LAKEKEEPER__KV2__USER admin Username to authenticate against the KV2 backend
LAKEKEEPER__KV2__PASSWORD password Password to authenticate against the KV2 backend
LAKEKEEPER__KV2__SECRET_MOUNT kv/data/iceberg Path to the secret mount in the KV2 backend

Nats

If you want the server to publish events to a NATS server, set the following environment variables:

Variable Example Description
LAKEKEEPER__NATS_ADDRESS nats://localhost:4222 The URL of the NATS server to connect to
LAKEKEEPER__NATS_TOPIC iceberg The subject to publish events to
LAKEKEEPER__NATS_USER test-user User to authenticate against nats, needs LAKEKEEPER__NATS_PASSWORD
LAKEKEEPER__NATS_PASSWORD test-password Password to authenticate against nats, needs LAKEKEEPER__NATS_USER
LAKEKEEPER__NATS_CREDS_FILE /path/to/file.creds Path to a file containing nats credentials
LAKEKEEPER__NATS_TOKEN xyz Nats token to authenticate against server

OpenID Connect

If you want to limit ac cess to the API, set LAKEKEEPER__OPENID_PROVIDER_URI to the URI of your OpenID Connect Provider. The catalog will then verify access tokens against this provider. The provider must have the .well-known/openid-configuration endpoint under ${LAKEKEEPER__OPENID_PROVIDER_URI}/.well-known/openid-configuration and the openid-configuration needs to have the jwks_uri and issuer defined.

If LAKEKEEPER__OPENID_PROVIDER_URI is set, every request needs have an authorization header, e.g.

curl {your-catalog-url}/catalog/v1/transactions/commit -X POST -H "authorization: Bearer {your-token-here}" -H "content-type: application/json" -d ...
Variable Example Description
LAKEKEEPER__OPENID_PROVIDER_URI https://keycloak.local/realms/{your-realm} OpenID Provider URL, with keycloak this is the url pointing to your realm, for Azure App Registration it would be something like https://login.microsoftonline.com/{your-tenant-id-here}/v2.0/. If this variable is not set, endpoints are not secured

License

Licensed under the Apache License, Version 2.0