Two-way sync
Changes in Azure Synapse Analytics or StarRocks instantly reflect in both systems. No stale data, no manual imports.
Keep Azure Synapse Analytics and StarRocks in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.
Stacksync syncs tables between Azure Synapse Analytics and StarRocks continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
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 Synapse Analytics objects | StarRocks objects | How this pairing syncs | |
|---|---|---|---|
| Views Curated projections used when downstream tools should not read base tables directly. | Views Logical views for shaping analytical reads. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Materialized views Precomputed aggregates that speed reads of frequently synced result sets. | Materialized views Automatically maintained rollups used to accelerate queries on synced data. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Schemas Namespaces that separate staging, integration, and presentation layers. | Columns Columnar storage with types mapped from source systems during sync. | Schemas is specific to Azure Synapse Analytics and Columns to StarRocks — each maps to any object or custom field on the other side. | |
| SQL pools Dedicated or serverless compute contexts that determine how and where queries run. | Databases Top-level namespaces addressed exactly as in MySQL clients. | SQL pools is specific to Azure Synapse Analytics and Databases to StarRocks — each maps to any object or custom field on the other side. | |
| Tables (dedicated SQL pool) Distributed warehouse tables that serve as sync destinations for analytics workloads. | Tables Defined with a table model (Primary Key, Unique Key, Aggregate, Duplicate Key) that determines update behavior. | Tables (dedicated SQL pool) is specific to Azure Synapse Analytics and Tables to StarRocks — each maps to any object or custom field on the other side. | |
| External tables Tables over files in the data lake, queried through serverless SQL and often read-only in syncs. | Partitions Time or range partitions that scope loads and retention. | External tables is specific to Azure Synapse Analytics and Partitions to StarRocks — each maps to any object or custom field on the other side. |
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.
DetectionStacksync polls Azure Synapse Analytics for changes on an incremental schedule, reading only records changed since the previous pass. Polling on watermark columns.
DeliveryEach detected change is applied to StarRocks as a row-level write, with types converted between the two schemas.
DetectionStacksync polls StarRocks for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling when reading.
DeliveryEach detected change is applied to Azure Synapse Analytics as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure Synapse Analytics–StarRocks connection.
Changes in Azure Synapse Analytics or StarRocks instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Azure Synapse Analytics or StarRocks data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Azure Synapse Analytics or StarRocks record.
Track your Azure Synapse Analytics ⇄ StarRocks sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Azure Synapse Analytics and StarRocks.
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.
Authenticate Azure Synapse Analytics and StarRocks with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Azure Synapse Analytics and StarRocks 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Azure Synapse Analytics and StarRocks: authenticate both systems, choose the objects to sync (such as Azure Synapse Analytics's Views and Materialized views), map fields visually, and changes propagate both ways in milliseconds — no code required.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Azure Synapse Analytics and StarRocks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Azure Synapse Analytics–StarRocks integration in-house.
Yes — Stacksync ships production-grade connectors for both Azure Synapse Analytics and StarRocks. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Azure Synapse Analytics: Polling on watermark columns; Synapse SQL pools do not expose log-based CDC for downstream consumers. On StarRocks: Query-based polling when reading; StarRocks is most often the destination side of a sync. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Azure Synapse Analytics side: Tables (dedicated SQL pool), External tables, Views, Schemas, plus custom fields where Azure Synapse Analytics exposes them. On the StarRocks side: Columns, Databases, Tables, Materialized views. Stacksync auto-detects both schemas and converts types between the two systems.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 469 integrations available for Azure Synapse Analytics and StarRocks.