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Database ⇄ Data warehouse

Azure SQL Database to Dremio integration — real-time, two-way sync

Keep Azure SQL Database and Dremio 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 Azure SQL Database and Dremio

Connect Azure SQL Database and Dremio with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Azure SQL Database's rows in Dremio, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Azure SQL Database where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Azure SQL Database sync into Dremio in real time, and result tables in Dremio sync back into Azure SQL Database, with schema and type mapping between the two systems handled for you.

Common use cases

  • 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.
  • Replicate Azure SQL tables to a warehouse without building custom CDC pipelines.
  • Consolidate data from several line-of-business apps into one Azure SQL database as an integration hub.

Offload heavy reads

Point analytical queries at the synced copy in Dremio and keep Azure SQL Database focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Azure SQL Database land in Dremio as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Dremio sync into Azure SQL Database, where whatever reads from that database gets them without querying the warehouse.

What you can sync between Azure SQL Database and Dremio

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.

Azure SQL Database objects Dremio objects
Rows and columns Standard relational records with typed columns; primary keys anchor upserts. Jobs Query execution records useful for monitoring sync workloads.
Stored procedures Existing business logic that some teams invoke on write instead of direct table inserts. Sources Connected storage and database systems (S3, ADLS, relational databases) Dremio queries in place.
Change tracking / CDC tables System-maintained change records used to drive incremental sync. Physical datasets Tables and files promoted from sources; the raw data a sync ultimately reads.
Tables The primary sync target; rows map one-to-one to records in the paired system. Virtual datasets (views) SQL views layering semantics over physical data; the preferred sync target for curated extracts.
Views Read-only projections used when the sync should expose a curated shape rather than raw tables. Apache Iceberg tables Lakehouse tables supporting DML and snapshot metadata usable for incremental reads.
Schemas Namespaces that organize tables and control which objects a sync user can reach. Spaces and folders Namespaces that organize virtual datasets and govern access.
What ships with Azure SQL Database ⇄ Dremio

Connect Azure SQL Database and Dremio for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure SQL Database or Dremio 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 Azure SQL Database or Dremio record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Azure SQL Database and Dremio.

How the Azure SQL Database and Dremio connectors work

Azure SQL Database

Integration surface
SQL wire protocol (TDS), the same protocol as SQL Server; T-SQL over standard drivers
Authentication
SQL authentication (database credentials) or Microsoft Entra ID authentication
Change detection
Change data capture or change tracking, both supported on Azure SQL Database; polling as a fallback
Capabilities
read · write · CDC

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
How it works

How to connect Azure SQL Database to Dremio — 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 Azure SQL Database and Dremio 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
    Azure SQL Database connected
    Dremio connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure SQL Database and Dremio 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 · Azure SQL Database ⇄ Dremio
    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
    Azure SQL Database Dremio
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure SQL Database and Dremio 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 Azure SQL Database and Dremio.

Popular · 8 of 386
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