Two-way sync
Changes in Cloudera Data Platform or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Keep Cloudera Data Platform 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.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Postgres Heroku's rows in Cloudera Data Platform, 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 Cloudera Data Platform in real time, and result tables in Cloudera Data Platform sync back into Postgres Heroku, with schema and type mapping between the two systems handled for you.
Rows from Postgres Heroku land in Cloudera Data Platform as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Cloudera Data Platform sync into Postgres Heroku, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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.
| Cloudera Data Platform objects | Postgres Heroku objects | |
|---|---|---|
| Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | JSONB Columns Semi-structured payloads for nested SaaS objects and metadata. | |
| Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | Sequences Generate surrogate keys for rows created by inbound syncs. | |
| Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. | Follower Databases Heroku-managed read replicas usable as low-impact sync sources. | |
| Views SQL views that can present curated, sync-ready projections of raw lake data. | Tables Standard Postgres tables; the primary two-way sync target for app data. | |
| Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | Views Read-side projections exposed to outbound syncs. | |
| Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. | Materialized Views Precomputed result sets synced outward on refresh. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cloudera Data Platform–Postgres Heroku connection.
Changes in Cloudera Data Platform or Postgres Heroku instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Cloudera Data Platform or Postgres Heroku data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Cloudera Data Platform or Postgres Heroku record.
Track your Cloudera Data Platform ⇄ Postgres Heroku sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Cloudera Data Platform and Postgres Heroku.
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 Cloudera Data Platform 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.
Pick the Cloudera Data Platform 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.
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 Cloudera Data Platform and Postgres Heroku: authenticate both systems, choose the objects to sync (such as Cloudera Data Platform's Impala tables and Kudu tables), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Cloudera Data Platform and Postgres Heroku. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Cloudera Data Platform: Polling via SQL on timestamp or partition columns; no consumer-facing change feed. 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. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Cloudera Data Platform side: Iceberg tables, Views, Partitions, Object store / HDFS files, plus custom fields where Cloudera Data Platform exposes them. On the Postgres Heroku side: Views, Materialized Views, Schemas, Primary and Unique Keys. 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.
Common patterns for Cloudera Data Platform and Postgres Heroku: Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed; Fresh analytics without loading windows. Rows from Postgres Heroku land in Cloudera Data Platform as they change, replacing hand-built CDC and batch extract jobs.
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 386 integrations available for Cloudera Data Platform and Postgres Heroku.