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SPECIFICTION
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AetherLake vs LavaLake

AetherLake

github.com

LavaLake

lavalake.io

Side by side

FigureAetherLakeLavaLake
Price fromFree€249/mo
Free planYesYes
Free trial—Yes
Open source——
WebYesYes
API—Yes
Self-hostedYesYes
Plans published24
Spec score · Data Lakehouse Platforms8.6 (#3)7.9 (#8)
DeploymentThe quick start lists Kubernetes, Helm 3.12 or later, kubectl, Docker, and an NGINX ingress controller as prerequisites.The reference deployment is a Docker Compose stack on one machine, with Ansible installation for Debian/Ubuntu; the Kubernetes Helm path has operational gaps including policy integration.
PurposeAetherLake is a Kubernetes-native data lakehouse that combines storage, catalog, federated SQL, stream processing, orchestration, BI, and identity in a web control panel.LavaLake combines a data warehouse and lakehouse with AI agents, SQL, and dashboards for deployment in a customer's own data center.

Plans

AetherLake

  • Internal, evaluation, and non-commercial useFree
  • Commercial licensePriced on request

AetherLake pricing →

LavaLake

  • CoreFree
  • Team€249 a month
  • Business€1,250 a month
  • Enterprise€2,499 a month

LavaLake pricing →

In their own words

AetherLake

AetherLake is a Kubernetes-native data lakehouse that brings storage, catalog, federated SQL, streaming, orchestration, BI, and identity into a web control panel. Its stack includes MinIO, Trino, Apache Polaris, Kafka, Flink, dbt, Airflow, Superset, Spark, Milvus, Prometheus, Grafana, PostgreSQL, and Keycloak. The panel shows pod health and resource use, supports service restarts, and provides workspaces for dbt, Kafka, Flink SQL, Trino queries, and Iceberg catalogs. Kafka and Flink are enabled by default; project examples describe streaming Kafka data into Iceberg tables and querying topics through Trino. Keycloak supplies OIDC single sign-on across services, with data-admin, data-scientist, and data-engineer roles. Deployment prerequisites include Kubernetes, Helm 3.12 or later, kubectl, Docker, and an NGINX ingress controller. Deployment materials cover AWS, Azure, and Google Cloud. An MCP server gives AI assistants access to platform status, logs and restarts, Trino queries, Polaris catalogs, and Airflow DAGs. The control panel is bilingual in English and Turkish. Internal, evaluation, development, testing, and non-commercial use is free; commercial use requires a separate license.

Visit github.com

LavaLake

LavaLake combines a data warehouse and lakehouse with SQL, dashboards and AI agents for deployment in a customer’s own data center. Its assistant can find data, query metrics and create dashboards using the signed-in user’s permissions. An MCP server lets external agents use platform tools under those permissions. Read-only database sources include PostgreSQL, MySQL, MS SQL Server, SAP Business One and SAP S/4HANA. CSV and DATEV files can be imported, while PDF, Word and text documents can be searched. Hybrid search combines vector and keyword results using a locally run nomic-embed-text model with PostgreSQL and pgvector. The lakehouse uses Apache Iceberg on S3-compatible storage, Nessie as its versioned catalog and Trino as its query engine. Tableau and Power BI connect through a read-only HTTP feed that applies analyst identity and records data fetches in an audit chain. The maker says lakehouse data and local search stay on the customer’s network, while external AI providers receive conversation content and assistant tool results. Core is free with no time limit; paid plans start at €249/mo.

Visit lavalake.io