Stream into Slack with your free account
Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.
- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT
Slack connector details
The Slack materialization connector sends data from Estuary Flow collections directly to Slack channels, enabling real-time alerts, notifications, and insights inside your workspace.
- Seamless integration: Deliver updates from Flow collections into any Slack channel
- Custom formatting: Configure sender name and emoji for easy identification
- Secure authentication: Connect using your Slack Access Token, Client ID, and Client Secret
- Automation-ready: Ideal for monitoring workflows, pipeline statuses, or anomaly alerts
- Flexible output: Supports multiple bindings to send different data streams to separate channels
- Secure deployment: Fully supported in Estuary’s Private and BYOC environments for governance and compliance
💡 Tip: Use this connector to automatically post data events or alerts to Slack — for example, notify your team when new records are ingested or errors are detected in a pipeline.
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.
Don't see a connector?Request and our team will get back to you in 24 hours
Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Speed | <100ms | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale |
Deliver real-time and batch data from DBs, SaaS, APIs, and more
Build Free Pipeline
