Use cases

Seven problems. One runtime.

Same connectors, same guarantees, seven different arguments. Pick the one closest to what you are building.

The Ledger Database replication Stream every insert, update, and delete from one database into another, in commit order, without a nightly dump and without writing a sync job. 2 of 5 connectors ship today The Meter Warehouse loading Feed Snowflake, BigQuery, Redshift, Databricks, or ClickHouse from your production database continuously, so the numbers an analyst reads are minutes old rather than a day old. 0 of 5 connectors ship today The Blueprint Lakehouse & Iceberg Write change data straight into S3, Iceberg, Parquet, Delta Lake, GCS, or Azure Data Lake, so the table format your query engine already reads is the one Zipline keeps current. 6 object store sinks The Post-mortem Event-driven services Turn database writes into a stream on Kafka, Pub/Sub, Kinesis, NATS, Pulsar, or RabbitMQ, so a service reacts to a change without polling and without a dual write. 0 dual writes required The Query Search index sync Push every row change into Elasticsearch or OpenSearch as it happens, so search results match the database instead of trailing a reindex job. Elasticsearch and OpenSearch on the roadmap The Timer Cache invalidation Drive Redis from the database change stream, so a cached value is dropped the moment its row changes instead of whenever its time to live happens to run out. 1 of 3 connectors ship today The Transcript AI agent context An agent reasoning over a warehouse snapshot from last night will confidently tell you about an order that shipped this morning. ClickHouse, S3 and Elasticsearch on the roadmap