Real-time
Two-way sync
Changes in Postgres Heroku or StarRocks instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ Data warehouse
Postgres Heroku to StarRocks integration — real-time, two-way sync
Keep Postgres Heroku 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.
- 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
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Postgres Heroku and StarRocks
Connect Postgres Heroku and StarRocks 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 Postgres Heroku's rows in StarRocks, 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 Postgres Heroku where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Postgres Heroku sync into StarRocks in real time, and result tables in StarRocks sync back into Postgres Heroku, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Land CRM and ERP records into StarRocks to serve low-latency operational dashboards
- 02 Continuously apply upserts from operational databases into Primary Key tables to keep analytics current
- 03 Expose CRM objects as Postgres tables the Heroku application can query and join directly
- 04 Sync Heroku Postgres into a warehouse for reporting without running ETL dynos
Common sync patterns
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Offload heavy reads
Point analytical queries at the synced copy in StarRocks and keep Postgres Heroku focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from Postgres Heroku land in StarRocks as they change, replacing hand-built CDC and batch extract jobs.
What you can sync between Postgres Heroku and StarRocks
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.
| Postgres Heroku objects | StarRocks objects | How this pairing syncs | |
|---|---|---|---|
| Tables Standard Postgres tables; the primary two-way sync target for app data. | 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. | |
| Views Read-side projections exposed to outbound syncs. | 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 result sets synced outward on refresh. | 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. | |
| Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | Columns Columnar storage with types mapped from source systems during sync. | Follower Databases is specific to Postgres Heroku and Columns to StarRocks — each maps to any object or custom field on the other side. | |
| Schemas Namespaces that scope which tables a sync reads and writes. | Databases Top-level namespaces addressed exactly as in MySQL clients. | Schemas is specific to Postgres Heroku and Databases to StarRocks — each maps to any object or custom field on the other side. | |
| Primary and Unique Keys Match keys for idempotent upserts from connected systems. | Partitions Time or range partitions that scope loads and retention. | Primary and Unique Keys is specific to Postgres Heroku and Partitions to StarRocks — each maps to any object or custom field on the other side. |
How changes propagate between Postgres Heroku and StarRocks
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.
Postgres Heroku StarRocks Interval-based propagation
DetectionStacksync polls Postgres Heroku for changes on an incremental schedule, reading only records changed since the previous pass. Trigger-based capture or polling in most configurations.
DeliveryEach detected change is applied to StarRocks as a row-level write, with types converted between the two schemas.
StarRocks Postgres Heroku Interval-based propagation
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 Postgres Heroku as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
- StarRocks: Ingestion throughput is bounded by cluster resources rather than API quotas.
What ships with Postgres Heroku ⇄ StarRocks
Connect Postgres Heroku and StarRocks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Postgres Heroku–StarRocks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Postgres Heroku or StarRocks 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 Postgres Heroku or StarRocks record.
Observability
Monitoring
Track your Postgres Heroku ⇄ StarRocks sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Postgres Heroku and StarRocks.
How the Postgres Heroku and StarRocks connectors work
Postgres Heroku
- Integration surface
- SQL wire protocol (standard PostgreSQL)
- Authentication
- Database credentials from the Heroku DATABASE_URL config var; SSL required
- Change detection
- Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings
- Capabilities
- read · write
- Rate limits
- No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan
StarRocks
- Integration surface
- MySQL wire protocol for SQL; HTTP-based Stream Load API for ingestion
- Authentication
- Database credentials (MySQL-compatible username/password)
- Change detection
- Query-based polling when reading; StarRocks is most often the destination side of a sync
- Capabilities
- read · write
- Rate limits
- Ingestion throughput is bounded by cluster resources rather than API quotas
How it works
How to connect Postgres Heroku to StarRocks — 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.
- 01
Connect your apps
Authenticate Postgres Heroku 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.
Postgres Heroku
connected
StarRocks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Postgres Heroku 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.
objects · Postgres Heroku ⇄ StarRocksCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Postgres Heroku StarRocksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Postgres Heroku and StarRocks integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Postgres Heroku and StarRocks: authenticate both systems, choose the objects to sync (such as Postgres Heroku's Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
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 Postgres Heroku and StarRocks records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Postgres Heroku and StarRocks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Postgres Heroku–StarRocks integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Postgres Heroku and StarRocks. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Postgres Heroku: Trigger-based capture or polling in most configurations; log-based logical replication availability depends on plan and Heroku's managed server settings. 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 StarRocks side: Partitions, Columns, Databases, Tables, plus custom fields where StarRocks exposes them. On the Postgres Heroku side: Primary and Unique Keys, JSONB Columns, Sequences, Follower Databases. Stacksync auto-detects both schemas and converts types between the two systems.
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.
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:
