Altertable docs

Altertable is an AI-native data platform for agents, apps, and humans. At its core is a context lakehouse built on DuckDB, bringing data, business definitions, and knowledge together.

Ingest records and files through SQL, APIs, or existing pipelines. Capture product analytics events with SDKs, or send logs, traces, and metrics through OpenTelemetry. Federate queries across existing databases, warehouses, and S3 buckets, leaving the data where it lives. Query and join ingested and external data with the same SQL engine.

Add business context through metrics, semantic models, documentation, and knowledge from your team so agents and humans can interpret the data. Use that shared context to investigate questions, build interactive data apps, and automate recurring work.

Databases, warehouses & object storage

Query via external catalogs

Files, records & ETL pipelines

Ingest to managed tables

Product events, logs, traces & metrics

Stream to managed tables

Context Lakehouse

DuckDB SQL
Lakehouse storage
Shared business context
Shared permissions

SQLHTTP APIMCP

Humans · SQL clients & BI

Data apps · APIs

Agents · MCP & tasks

Get started

Choose a quickstart to connect or ingest data, track product events, or send telemetry. You can follow the steps yourself or use an agent to guide the setup.

Ingest your first data

Append a small record to an Altertable table with the CLI, query it to verify ingestion, and continue with file uploads or an agent-led setup.

Connect an existing source

Connect a database, warehouse, or object-storage catalog to Altertable, inspect its tables, and verify a query without copying data into managed tables.

Track a product event

Enable Product Analytics, send a test event with an API key, and verify it in the lakehouse before instrumenting your application with an SDK.

Send logs and traces

Enable OpenTelemetry in Altertable, configure an exporter for logs or traces, and verify recent telemetry from your service with SQL.