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Data warehouse ⇄ Business productivity

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

Keep Dremio and GitHub 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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Why teams connect Dremio and GitHub

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

Whatever GitHub 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 Organizations and Teams, Users, Labels and Milestones, Repositories from GitHub 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 GitHub where the tool can use them.

Common use cases

  • 01 Publish release data into customer-communication tools when a new version ships.
  • 02 Two-way sync of GitHub issues with Jira, Linear, or a support system so engineering and customer-facing teams work in their own tools.
  • 03 Reverse-ETL aggregates computed over lake data out to CRMs and finance tools for business users.
  • 04 Publish operational database tables into Iceberg via Dremio so the lakehouse reflects current application state.

Common sync patterns

Cross-tool reporting

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

Where GitHub accepts updates: operational write-back

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

History that outlives the tool

A continuously synced copy in Dremio preserves a queryable record even as data ages out of GitHub or gets changed inside it.

What you can sync between Dremio and GitHub

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 GitHub objects How this pairing syncs
Jobs Query execution records useful for monitoring sync workloads. Commits Read-only history used to link code activity to tickets and releases. Jobs is specific to Dremio and Commits to GitHub — each maps to any object or custom field on the other side.
Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place. Releases Tagged versions synced into changelogs, CRMs, or customer-notification systems. Sources is specific to Dremio and Releases to GitHub — each maps to any object or custom field on the other side.
Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads. Workflow runs (Actions) CI results synced into incident and reporting systems. Physical datasets is specific to Dremio and Workflow runs (Actions) to GitHub — each maps to any object or custom field on the other side.
Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts. Organizations and Teams Membership data synced with identity systems and HR directories for access reviews. Virtual datasets (views) is specific to Dremio and Organizations and Teams to GitHub — each maps to any object or custom field on the other side.
Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads. Users Author and assignee identities matched to internal directories. Apache Iceberg tables is specific to Dremio and Users to GitHub — each maps to any object or custom field on the other side.
Spaces and folders Namespaces that organize virtual datasets and govern access. Labels and Milestones Classification fields mapped to statuses and sprints in external trackers. Spaces and folders is specific to Dremio and Labels and Milestones to GitHub — each maps to any object or custom field on the other side.

How changes propagate between Dremio and GitHub

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Dremio GitHub Interval-based propagation

DetectionStacksync polls Dremio for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL.

DeliveryEach detected change is written to GitHub through its API, with automatic retries and rate-limit backoff.

GitHub Dremio Sub-second propagation

DetectionGitHub notifies Stacksync of record changes through webhook events. Webhooks with a broad event catalog covering issues, pull requests, pushes, and releases.

DeliveryEach detected change is applied to Dremio as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Dremio: Bounded by engine capacity and workload management rather than API rate limits.
  • GitHub: Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.
What ships with Dremio ⇄ GitHub

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Dremio or GitHub 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 GitHub record.

Observability

Monitoring

Track your Dremio ⇄ GitHub 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 GitHub.

How the Dremio and GitHub 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

GitHub

Integration surface
REST API and GraphQL API
Authentication
OAuth 2.0, fine-grained personal access tokens, or GitHub App installation tokens
Change detection
Webhooks with a broad event catalog covering issues, pull requests, pushes, and releases; polling for backfill
Capabilities
read · write · webhooks
Rate limits
Authenticated REST requests are limited to 5,000 per hour per user; GitHub Apps scale limits per installation.
How it works

How to connect Dremio to GitHub — 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 GitHub 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
    GitHub connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Dremio and GitHub 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 ⇄ GitHub
    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 GitHub
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Dremio and GitHub integration FAQ

SECURITY

Security teams trust 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
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 385 integrations available for Dremio and GitHub.

Popular · 8 of 385
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