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Data warehouse ⇄ Business productivity

Dremio to Slack integration — real-time, two-way sync

Keep Dremio and Slack in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Migrated from Mulesoft
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Why teams connect Dremio and Slack

Get the data locked inside Slack into Dremio as live tables, and send results back where Slack can use them, without writing a pipeline.

Whatever Slack is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.

Stacksync syncs Channels, Messages, Threads, Users from Slack into tables in Dremio continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Dremio can also be written back into fields in Slack where the tool can use them.

Common use cases

  • Archive channel messages into a warehouse or database for compliance and analytics
  • Create or update records in a database when specific messages or reactions occur in a channel
  • Sync curated Dremio views into an operational Postgres so applications get low-latency access to lakehouse data.
  • Reverse-ETL aggregates computed over lake data out to CRMs and finance tools for business users.

Analytics on Slack's data

Records and events from Slack land in Dremio as queryable tables, current within seconds and ready to join with the rest of the warehouse.

Cross-tool reporting

Combine Slack's data with data from every other synced system to answer questions no single tool can.

Where Slack accepts updates: operational write-back

Segments, scores, or reference values computed in Dremio sync back onto records in Slack, putting analysis where the work happens.

What you can sync between Dremio and Slack

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Dremio objects Slack objects
Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. Channels Conversations (public, private, DMs) that messages are read from and posted to.
Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. Messages Keyed by channel and timestamp; posted via chat.postMessage and read via history methods.
Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. Threads Replies grouped under a parent message timestamp, preserved when archiving conversations.
Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. Users Workspace members with profile fields, synced against HR systems and identity providers.
Spaces and folders Namespaces that organize virtual datasets and govern access. User groups Handles like @support that map to teams in external systems.
Reflections Materialized accelerations that make repeated extraction queries cheaper. Files Uploads attached to messages, retrievable for archiving.
What ships with Dremio ⇄ Slack

Connect Dremio and Slack for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Dremio–Slack connection.

Real-time

Two-way sync

Changes in Dremio or Slack instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Dremio or Slack data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Dremio or Slack record.

Observability

Monitoring

Track your Dremio ⇄ Slack sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Dremio and Slack.

How the Dremio and Slack connectors work

Dremio

Integration surface
Arrow Flight SQL, JDBC/ODBC, and a REST API
Authentication
Personal access tokens or username/password; OAuth-based SSO on Dremio Cloud
Change detection
Polling via SQL; Iceberg table snapshots can anchor incremental reads; no consumer-facing change feed
Capabilities
read · write
Rate limits
Bounded by engine capacity and workload management rather than API rate limits

Slack

Integration surface
Web API (HTTP RPC-style methods) plus the Events API
Authentication
OAuth 2.0 with bot or user tokens and granular scopes
Change detection
Events API webhooks, delivered over HTTP callbacks or Socket Mode
Capabilities
read · write · webhooks
Rate limits
Per-method rate limit tiers; message posting is additionally limited per channel
How it works

How to connect Dremio to Slack — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Dremio and Slack with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Dremio connected
    Slack connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Dremio and Slack objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Dremio ⇄ Slack
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Dremio Slack
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Dremio and Slack integration FAQ

SECURITY

Security teams love Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Dremio and Slack.

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