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Capture data from Slack and deliver it to your destinations using Estuary's pre-built connectors. Build pipelines for real-time, incremental, or batch data movement based on connector capabilities.
- <100ms to batch
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Slack connector details
The Slack capture connector in Estuary captures workspace data from Slack through its APIs and loads each selected resource into an Estuary collection. It supports conversations, messages, users, files, threads, and related workspace data for downstream analytics, search, archiving, and other data workflows.
- API-based data capture from Slack
- Supports Channels (Conversations) and Channel Members
- Captures Messages and Threads
- Supports Users and User Groups
- Captures Files and Remote Files
- Separate Estuary collections for each selected Slack resource
- Configurable start date to determine how far back Slack data is replicated
- Configurable thread lookback window for retrieving historical thread messages
- Option to automatically join available channels
- Slack workspace or API-token authentication, with OAuth supported in connector configuration
The start date determines the earliest Slack data Estuary will replicate, while the thread lookback window controls how far back the connector searches for messages in conversation threads. Each enabled Slack resource is mapped to a separate Estuary collection by default.
See how Deel uses Slack
How to connect Slack to your destination in 3 easy steps
- 1
Connect Slack as your data source
Securely connect Slack and choose the objects, tables, or collections you need to sync.
- 2
Prepare and transform your data
Apply transformations and schema mapping as data moves whether you are streaming in real time or loading in batches.
- 3
Deliver to your destination
Continuously or periodically deliver your data to the destination you choose, based on the capabilities and configuration of your pipeline.
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Dive deeper into Slack with tutorials and walkthroughs from our YouTube channel.
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HIGH THROUGHPUT
Distributed, event-driven architecture scales for demanding data workloads.
DURABLE COLLECTIONS
Store data as it moves so you can transform, replay, and deliver it downstream.
FLEXIBLE LATENCY
From <100ms CDC and real-time streaming to scheduled batch, depending on connector capabilities.
From <100ms to batch
Estuary supports CDC, real-time streaming, incremental syncs, and scheduled batch across its connector ecosystem. Capture data from Slack using the cadence supported by the connector, then transform and deliver it to the destinations your team uses.
- Connect Slack to warehouses, databases, data lakes, search platforms, and event systems through Estuary-supported destinations.
- Capture once and reuse Slack data across transformations and multiple downstream destinations without rebuilding source extraction.
See where you can send Slack data:
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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | Kafka | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Latency | <100ms to scheduled | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale | ||||
| Maintenance Effort | Low | Medium | High | High |
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