Two-way sync
Changes in Cloudera Data Platform or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Keep Cloudera Data Platform and PostgreSQL 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 PostgreSQL'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 PostgreSQL where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in PostgreSQL sync into Cloudera Data Platform in real time, and result tables in Cloudera Data Platform sync back into PostgreSQL, with schema and type mapping between the two systems handled for you.
Rows from PostgreSQL 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 PostgreSQL, 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 | PostgreSQL objects | |
|---|---|---|
| Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | Views Read-side projections used to expose joined or filtered data to a sync. | |
| 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 a refresh schedule. | |
| Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Schemas Namespaces that scope which tables a sync reads and writes. | |
| Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | Columns Field-level mapping targets; types are mapped to the connected system's field types. | |
| Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Primary and Unique Keys Used as match keys for idempotent upserts and conflict resolution. | |
| Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | JSONB Columns Hold semi-structured payloads such as nested SaaS objects or metadata. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cloudera Data Platform–PostgreSQL connection.
Changes in Cloudera Data Platform or PostgreSQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Cloudera Data Platform or PostgreSQL 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 PostgreSQL record.
Track your Cloudera Data Platform ⇄ PostgreSQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Cloudera Data Platform and PostgreSQL.
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 PostgreSQL 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 PostgreSQL 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 PostgreSQL: authenticate both systems, choose the objects to sync (such as Cloudera Data Platform's Partitions and Object store / HDFS files), map fields visually, and changes propagate both ways in milliseconds — no code required.
Cloudera Data Platform: JDBC/ODBC over Hive and Impala SQL endpoints, plus REST management APIs. Authentication: Kerberos, LDAP, or workload user credentials, often brokered through the Knox gateway. PostgreSQL: SQL wire protocol (PostgreSQL frontend/backend protocol). Authentication: Database credentials (connection string or parameters), with optional SSL root certificate upload and optional SSH tunnel (SSH user + host); a least-privilege DB user. Stacksync manages authentication, retries, and rate limits on both sides.
Cloudera Data Platform: CDP bundles open-source engines (Hive, Impala, Spark, Kudu) behind a shared Hive Metastore and shared security via Apache Ranger, so integrations usually target a SQL endpoint rather than storage directly. PostgreSQL: INSERT ... ON CONFLICT gives native upsert semantics, which makes inbound syncs idempotent against primary or unique keys. Stacksync's field mapping accounts for these differences between Cloudera Data Platform and PostgreSQL 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 Cloudera Data Platform and PostgreSQL records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Cloudera Data Platform and PostgreSQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Cloudera Data Platform–PostgreSQL integration in-house.
Yes — Stacksync ships production-grade connectors for both Cloudera Data Platform and PostgreSQL. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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 PostgreSQL.