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AI ⇄ Data warehouse

Azure OpenAI to Azure Synapse Analytics integration — real-time data sync

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

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

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Why teams connect Azure OpenAI and Azure Synapse Analytics

Flow Azure OpenAI data into Azure Synapse Analytics in real time — no exports, no schedulers, no custom scripts.

Azure OpenAI is a read-only source: Stacksync reads its data in real time and delivers it into Azure Synapse Analytics, so Azure Synapse Analytics always reflects the current state of Azure OpenAI — without exports, scripts, or schedulers.

Azure Synapse Analytics holds the raw records the business runs on; Azure OpenAI turns those records into embeddings, scores, labels, and summaries. The two meet wherever a warehouse row needs to be enriched by a model and the result needs somewhere durable to live. Most teams stitch that meeting together with export scripts and a queue, then spend their time keeping the glue alive.

The payoff is that model output stops living in a separate place from the data it describes. Once results sit in Azure Synapse Analytics, they join against billing, product, and usage tables already there, so you can report on quality, cost, and coverage without moving anything by hand.

Common use cases

  • 01 Sync the Deployments inventory (model, version, TPM capacity) into Postgres so platform teams track every Azure OpenAI deployment across subscriptions in SQL.
  • 02 Land Fine-tuning jobs with their status, base model, and result Files in a warehouse to power MLOps dashboards without per-viewer API calls.
  • 03 Consolidate SaaS data alongside lake data so analysts join both through one SQL surface.
  • 04 Load CRM and ERP records into Synapse dedicated SQL pool tables for enterprise reporting.

Common sync patterns

Model output back in the warehouse

Scores, labels, embeddings, or summaries produced in Azure OpenAI land in Azure Synapse Analytics as columns or tables, queryable and joinable with the rest of the business data.

Keep an index in step with the source

As records change in Azure Synapse Analytics, matching Assistants, Vector stores, Deployments, Models in Azure OpenAI are inserted, updated, or removed, so what Azure OpenAI serves reflects the warehouse instead of a stale snapshot.

One place to analyze AI results

Combine Azure OpenAI's output with the tables already in Azure Synapse Analytics to report on model quality, cost, and coverage without exporting anything to a spreadsheet.

What you can sync between Azure OpenAI and Azure Synapse Analytics

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 OpenAI objects Azure Synapse Analytics objects How this pairing syncs
Usage and quota Per-deployment TPM/RPM consumption and remaining quota, read from usage endpoints and Azure Monitor for cost and throttling reporting. Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. Usage and quota is specific to Azure OpenAI and Tables (dedicated SQL pool) to Azure Synapse Analytics — each maps to any object or custom field on the other side.
Assistants Persistent assistants (preview) with instructions, tools, and linked files; read as configuration inventory, not authored via sync. External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. Assistants is specific to Azure OpenAI and External tables to Azure Synapse Analytics — each maps to any object or custom field on the other side.
Vector stores File collections (preview) backing file-search retrieval; read as metadata such as name, file counts, and status. Views Curated projections used when downstream tools should not read base tables directly. Vector stores is specific to Azure OpenAI and Views to Azure Synapse Analytics — each maps to any object or custom field on the other side.
Deployments Named model deployments (model, version, SKU, assigned TPM capacity) read as a control-plane inventory via Azure Resource Manager; read-only in sync. Schemas Namespaces that separate staging, integration, and presentation layers. Deployments is specific to Azure OpenAI and Schemas to Azure Synapse Analytics — each maps to any object or custom field on the other side.
Models Catalog of base and fine-tunable models available per region; read-only reference data used to resolve deployment and fine-tuning targets. Materialized views Precomputed aggregates that speed reads of frequently synced result sets. Models is specific to Azure OpenAI and Materialized views to Azure Synapse Analytics — each maps to any object or custom field on the other side.
Fine-tuning jobs Training jobs with status, base model, hyperparameters, and result files; status is polled from queued through succeeded or failed. SQL pools Dedicated or serverless compute contexts that determine how and where queries run. Fine-tuning jobs is specific to Azure OpenAI and SQL pools to Azure Synapse Analytics — each maps to any object or custom field on the other side.

How changes propagate between Azure OpenAI and Azure Synapse Analytics

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.

Azure OpenAI Azure Synapse Analytics Interval-based propagation

DetectionStacksync polls Azure OpenAI for changes on an incremental schedule, reading only records changed since the previous pass. Polling: list endpoints plus GET on job IDs for status.

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

Azure Synapse Analytics Azure OpenAI Interval-based propagation

DetectionStacksync polls Azure Synapse Analytics for changes on an incremental schedule, reading only records changed since the previous pass. Polling on watermark columns.

DeliveryAzure OpenAI does not accept inbound record writes, so this direction carries requests rather than records: Azure OpenAI's output flows back as field updates on the originating Azure Synapse Analytics records.

Rate-limit considerations

  • Azure OpenAI: Per-deployment TPM and RPM limits (about 6 RPM per 1000 TPM), scoped by region and subscription; control-plane ARM calls throttle separately.
What ships with Azure OpenAI ⇄ Azure Synapse Analytics

Connect Azure OpenAI and Azure Synapse Analytics for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure OpenAI–Azure Synapse Analytics connection.

Real-time

Real-time sync

Changes in Azure OpenAI or Azure Synapse Analytics instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure OpenAI or Azure Synapse Analytics 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 OpenAI or Azure Synapse Analytics record.

Observability

Monitoring

Track your Azure OpenAI ⇄ Azure Synapse Analytics sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Azure OpenAI and Azure Synapse Analytics.

How the Azure OpenAI and Azure Synapse Analytics connectors work

Azure OpenAI

Integration surface
REST data-plane (inference + authoring) and Azure Resource Manager control-plane
Authentication
API key in the api-key header, or a Microsoft Entra ID bearer token / managed identity
Change detection
Polling: list endpoints plus GET on job IDs for status; no webhooks or change feed. Fine-tuning and batch jobs expose queued/running/succeeded states.
Capabilities
read
Rate limits
Per-deployment TPM and RPM limits (about 6 RPM per 1000 TPM), scoped by region and subscription; control-plane ARM calls throttle separately.

Azure Synapse Analytics

Integration surface
SQL wire protocol (TDS) with T-SQL for SQL pools; additional Spark and pipeline surfaces exist but syncs use the SQL endpoint
Authentication
SQL authentication or Microsoft Entra ID
Change detection
Polling on watermark columns; Synapse SQL pools do not expose log-based CDC for downstream consumers
Capabilities
read · write
How it works

How to connect Azure OpenAI to Azure Synapse Analytics — 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 OpenAI and Azure Synapse Analytics 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 OpenAI connected
    Azure Synapse Analytics connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure OpenAI and Azure Synapse Analytics 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 OpenAI ⇄ Azure Synapse Analytics
    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 OpenAI Azure Synapse Analytics
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure OpenAI and Azure Synapse Analytics integration FAQ

SECURITY

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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.

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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 514 integrations available for Azure OpenAI and Azure Synapse Analytics.

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