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Lakehouse
Ingest or connect?

Ingest or connect?

Ingest data to copy records or files into Altertable-managed tables. Connect an external catalog to query data where it already lives. You can use both and join their tables with SQL.

Choose a route

Your dataRouteWhere the queried data lives
Existing database or warehouseExternal catalogIn the source system
Files, Iceberg datasets, or managed table catalogs in object storageQuery object storageIn your bucket or table catalog
Local CSV, JSON, or Parquet filesUpload filesIn managed lakehouse tables
New files arriving in a bucketBucket synchronizerCopied into managed tables on a schedule
Application records or backend eventsAppend or upsertIn managed lakehouse tables
DataFrames or local DuckDB resultsDataFrame ingestion or DuckDB ingestionIn managed lakehouse tables
Product behavior and user identitiesProduct Analytics SDK or APIIn the Product Analytics catalog
Application logs and tracesOpenTelemetry SDK or collectorIn the OpenTelemetry catalog
Existing data pipelinesPipeline integrationDepends on the integration

Connecting a source does not schedule a copy of its data. Query freshness and performance depend on the source. A bucket synchronizer copies new files into managed tables on its configured schedule.

Choose the ingestion operation

  • Append for new JSON records. Altertable can create missing tables and add columns.
  • Upload to create a table from a file or append file rows. Use overwrite only when you intend to replace the table.
  • Upsert to insert new rows and update matching rows by a primary key.

See the ingestion guide for working examples and the HTTP API reference for request limits and exact behavior.

Ask your agent to choose

Agent prompt
Read https://altertable.ai/docs/lakehouse/ingest-or-connect.md for context. Help me choose how to bring my data to Altertable. Ask where it lives, whether it must stay there, and how fresh it needs to be. Recommend a supported ingestion or external-catalog route and explain what gets copied.