Storing and querying data

Data warehouses and data lakes are primary destinations for Snowplow data. For other options, see the destinations overview page.

Data warehouse loaders

Cloud

The cloud selection is for where your Snowplow pipeline runs. The warehouse itself can be deployed in any cloud.

AWS
GCP
Azure

Destination	Type	Loader application	Status
Redshift (including Redshift serverless)	Batching (recommended) or micro-batching	RDB Loader	Production-ready
BigQuery	Streaming	BigQuery Loader	Production-ready
Snowflake	Streaming	Snowflake Streaming Loader	Production-ready
Databricks	Batching (recommended) or micro-batching	Snowplow RDB Loader	Production-ready

Destination	Type	Loader application	Status
BigQuery	Streaming	BigQuery Loader	Production-ready
Snowflake	Streaming	Snowflake Streaming Loader	Production-ready
Databricks	Micro-batching (via a data lake)	Lake Loader	Production-ready

Destination	Type	Loader application	Status
BigQuery	Streaming	BigQuery Loader	Production-ready
Snowflake	Streaming	Snowflake Streaming Loader	Production-ready
Databricks	Micro-batching (via a data lake)	Lake Loader	Production-ready
Synapse Analytics	Micro-batching (via a data lake)	Lake Loader	Production-ready

Data lake loaders

All lake loaders are micro-batching.

AWS
GCP
Azure

Lake	Format	Compatibility	Loader application	Status
S3	Delta	Athena, ~~Databricks~~	Lake Loader	Production-ready
S3	Iceberg	Athena, Redshift	Lake Loader	Production-ready
S3	TSV/JSON	Athena	S3 Loader	Only recommended for use with RDB Batch Transformer or for raw failed events

tip

Please note that currently the S3 Delta loader is not compatible with Databricks. The loader uses DynamoDB tables for mutually exclusive writes to S3, a feature of Delta. Databricks, however, does not support this (as of July 2025). This means that it’s not possible to alter the data via Databricks (e.g. to run OPTIMIZE or to delete PII).

Data warehouse loaders​

Data lake loaders​

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Data warehouse loaders

Data lake loaders