Real-time
Two-way sync
Changes in Apache Pinot or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Apache Pinot to Postgres Heroku integration — real-time, two-way sync
Keep Apache Pinot and Postgres Heroku 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 Apache Pinot and Postgres Heroku
Connect Postgres Heroku and Apache Pinot 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 Apache Pinot, 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 Apache Pinot in real time, and result tables in Apache Pinot sync back into Postgres Heroku, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Serve user-facing analytics from Pinot while syncing daily rollups to finance and ops tools.
- 02 Keep upsert-enabled real-time tables aligned with mutable operational records streamed from source systems.
- 03 Reflect billing and subscription records into the app database so product logic reads local rows
- 04 Expose CRM objects as Postgres tables the Heroku application can query and join directly
Common sync patterns
Offload heavy reads
Point analytical queries at the synced copy in Apache Pinot and keep Postgres Heroku focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from Postgres Heroku land in Apache Pinot as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Apache Pinot sync into Postgres Heroku, where whatever reads from that database gets them without querying the warehouse.
What you can sync between Apache Pinot and Postgres Heroku
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 Pinot objects | Postgres Heroku objects | How this pairing syncs | |
|---|---|---|---|
| Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. | Tables Standard Postgres tables; the primary two-way sync target for app data. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. | Schemas Namespaces that scope which tables a sync reads and writes. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tenants Logical groupings that isolate workloads on shared clusters. | Materialized Views Precomputed result sets synced outward on refresh. | Tenants is specific to Apache Pinot and Materialized Views to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Segments Immutable data files that batch ingestion uploads and the cluster serves. | Primary and Unique Keys Match keys for idempotent upserts from connected systems. | Segments is specific to Apache Pinot and Primary and Unique Keys to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | Real-time Tables is specific to Apache Pinot and JSONB Columns to Postgres Heroku — each maps to any object or custom field on the other side. | |
| Offline Tables Batch-loaded tables merged with real-time data at query time. | Sequences Generate surrogate keys for rows created by inbound syncs. | Offline Tables is specific to Apache Pinot and Sequences to Postgres Heroku — each maps to any object or custom field on the other side. |
How changes propagate between Apache Pinot and Postgres Heroku
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.
Apache Pinot Postgres Heroku Interval-based propagation
DetectionStacksync polls Apache Pinot for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Pinot via streaming ingestion or segment upload, not row-level writes.
DeliveryEach detected change is applied to Postgres Heroku as a row-level write, with types converted between the two schemas.
Postgres Heroku Apache Pinot 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 Apache Pinot as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Apache Pinot: No fixed API quotas; query throughput depends on broker and server sizing.
- Postgres Heroku: No API rate limits; connection counts and performance are bounded by the Heroku Postgres plan.
What ships with Apache Pinot ⇄ Postgres Heroku
Connect Apache Pinot and Postgres Heroku for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Pinot–Postgres Heroku connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Pinot or Postgres Heroku 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 Apache Pinot or Postgres Heroku record.
Observability
Monitoring
Track your Apache Pinot ⇄ Postgres Heroku sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Apache Pinot and Postgres Heroku.
How the Apache Pinot and Postgres Heroku connectors work
Apache Pinot
- Integration surface
- REST API (SQL queries via the broker; administration via the controller); JDBC client available
- Authentication
- Deployment-dependent: HTTP basic authentication or token-based auth where enabled
- Change detection
- Not applicable for reads out (polling by time column); data enters Pinot via streaming ingestion or segment upload, not row-level writes
- Capabilities
- read · write
- Rate limits
- No fixed API quotas; query throughput depends on broker and server sizing
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
How it works
How to connect Apache Pinot to Postgres Heroku — 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 Apache Pinot and Postgres Heroku with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Apache Pinot
connected
Postgres Heroku
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Pinot and Postgres Heroku 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 · Apache Pinot ⇄ Postgres HerokuCustomers 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.
Apache Pinot Postgres HerokuCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Pinot and Postgres Heroku integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Apache Pinot and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Apache Pinot's Tables and Schemas), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Apache Pinot: REST API (SQL queries via the broker; administration via the controller); JDBC client available. Authentication: Deployment-dependent: HTTP basic authentication or token-based auth where enabled. Postgres Heroku: SQL wire protocol (standard PostgreSQL). Authentication: Database credentials from the Heroku DATABASE_URL config var; SSL required. Stacksync manages authentication, retries, and rate limits on both sides.
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Apache Pinot: Pinot separates offline and real-time tables and merges them at query time through the broker, so one logical table can span batch history and fresh stream data. Postgres Heroku: Heroku Postgres is standard PostgreSQL, so any Postgres client, driver, or SQL tool connects unchanged. Stacksync's field mapping accounts for these differences between Apache Pinot and Postgres Heroku without custom code.
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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 Pinot and Postgres Heroku records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Pinot and Postgres Heroku connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Pinot–Postgres Heroku integration in-house.
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Yes — Stacksync ships production-grade connectors for both Apache Pinot and Postgres Heroku. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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:
Related integrations
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