Two-way sync
Changes in Apache Doris or StarRocks instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Doris 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 Apache Doris 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.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
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.
| Apache Doris objects | StarRocks objects | How this pairing syncs | |
|---|---|---|---|
| Databases Logical containers that scope connections and grants. | Databases Top-level namespaces addressed exactly as in MySQL clients. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tables Columnar tables in one of Doris's table models, used as sync destinations. | Tables Defined with a table model (Primary Key, Unique Key, Aggregate, Duplicate Key) that determines update behavior. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Partitions Range or list partitions that bound incremental loads. | Partitions Time or range partitions that scope loads and retention. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Materialized Views Precomputed views readable for downstream syncs and BI. | 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. | |
| Users and Roles Principals used to grant the sync connection scoped access. | Views Logical views for shaping analytical reads. | Users and Roles is specific to Apache Doris and Views to StarRocks — each maps to any object or custom field on the other side. | |
| Unique Key Tables Tables supporting primary-key upserts, the natural target for row-level syncs. | Columns Columnar storage with types mapped from source systems during sync. | Unique Key Tables is specific to Apache Doris and Columns 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 Apache Doris for changes on an incremental schedule, reading only records changed since the previous pass. Polling on partition or timestamp columns for reads.
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 Apache Doris as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Doris–StarRocks connection.
Changes in Apache Doris or StarRocks instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Doris 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 Apache Doris or StarRocks record.
Track your Apache Doris ⇄ StarRocks sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Doris 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 Apache Doris 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 Apache Doris 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 Apache Doris and StarRocks: authenticate both systems, choose the objects to sync (such as Apache Doris's Databases and Tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Apache Doris: Tables follow explicit data models (duplicate, aggregate, unique key), and the unique key model supports primary-key upserts suited to syncing mutable records. StarRocks: It speaks the MySQL wire protocol, so standard MySQL clients, drivers, and BI tools connect without a special driver. Stacksync's field mapping accounts for these differences between Apache Doris and StarRocks without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Apache Doris and StarRocks records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Doris and StarRocks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Doris–StarRocks integration in-house.
Yes — Stacksync ships production-grade connectors for both Apache Doris and StarRocks. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Apache Doris: Polling on partition or timestamp columns for reads; ingestion into Doris is push-based via load jobs. 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.
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 364 integrations available for Apache Doris and StarRocks.