01. Select a source02. Transform in-flight03. Deliver to Slack
Slack connector details
The Slack materialization connector in Estuary Flow delivers data from your pipelines directly into your destination system — continuously and in real time. Using merge-based writes, Flow efficiently updates only changed records, ensuring your destination stays perfectly in sync without unnecessary reprocessing. Whether for analytics, AI, or operational use cases, Estuary Flow provides a reliable, cost-efficient way to keep Slack up to date.
Log-based CDC for high-performance, low-impact data capture
Automatic schema evolution to handle changes in source structure without manual intervention
Unified streaming and batch ingestion in the same pipeline
Hybrid deployment and BYOC support for security and control
Fault-tolerant pipelines that resume automatically from the last checkpoint
Kafka API connectivity for direct integration into streaming ecosystems
For more details about the Slack connector, check out the documentation page.
HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.
DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.
REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes to Slack in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
Ensure your Slack insights always reflect the latest data by connecting your databases to Slack with change data capture.
Or connect critical SaaS apps to Slack with real-time data pipelines.
