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Version: 0.3.25

Destinations

Pick one of our high quality destinations and load your data to a local database, warehouse or a data lake. Append, replace or merge your data. Apply performance hints like partitions, clusters or indexes. Load directly or via staging. Each of our destinations goes through few hundred automated tests every day.

Destination or feature missing? Join our Slack community and ask for it
Need more info? Join our Slack community and ask in the tech help channel or Talk to an engineer

Otherwise pick a destination below:

📄️ Google BigQuery

Google BigQuery `dlt` destination

📄️ DuckDB

DuckDB `dlt` destination

📄️ Microsoft SQL Server

Microsoft SQL Server `dlt` destination

📄️ Filesystem & buckets

Filesystem destination stores data in remote file systems and bucket storages like S3, google storage or azure blob storage. Underneath it uses fsspec to abstract file operations. Its primary role is to be used as a staging for other destinations but you can also quickly build a data lake with it.

📄️ Postgres

Postgres `dlt` destination

📄️ Amazon Redshift

Amazon Redshift `dlt` destination

📄️ Snowflake

Snowflake `dlt` destination

📄️ AWS Athena / Glue Catalog

AWS Athena `dlt` destination

📄️ 🧪 MotherDuck

MotherDuck `dlt` destination

📄️ Weaviate

Weaviate is an open source vector database that can be used as a destination in dlt.

📄️ Qdrant

Qdrant is a high-performance vector search engine/database that can be used as a destination in dlt.

This demo works on codespaces. Codespaces is a development environment available for free to anyone with a Github account. You'll be asked to fork the demo repository and from there the README guides you with further steps.

The demo uses the Continue VSCode extension.

Off to codespaces!

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