Two-way sync
Changes in Amazon RDS or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon RDS and Cloudera Data Platform 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 Amazon RDS'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 Amazon RDS where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Amazon RDS sync into Cloudera Data Platform in real time, and result tables in Cloudera Data Platform sync back into Amazon RDS, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Cloudera Data Platform and keep Amazon RDS focused on its operational workload.
Rows from Amazon RDS 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 Amazon RDS, where whatever reads from that database gets them without querying the warehouse.
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.
| Amazon RDS objects | Cloudera Data Platform objects | |
|---|---|---|
| Views Read-side projections exposed to outbound syncs. | Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | |
| Columns Field-level mapping targets, typed per the underlying engine. | Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | |
| Primary and Unique Keys Match keys for idempotent upserts. | Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | |
| Read Replicas Low-impact read endpoints often used as the source side of a sync. | Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. | |
| Stored Procedures Engine-specific logic that can react to synced rows. | Views SQL views that can present curated, sync-ready projections of raw lake data. | |
| Databases Engine-level databases on the instance that scope a sync's reads and writes. | Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon RDS–Cloudera Data Platform connection.
Changes in Amazon RDS or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon RDS or Cloudera Data Platform data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon RDS or Cloudera Data Platform record.
Track your Amazon RDS ⇄ Cloudera Data Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon RDS and Cloudera Data Platform.
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 Amazon RDS and Cloudera Data Platform 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 Amazon RDS and Cloudera Data Platform 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 Amazon RDS and Cloudera Data Platform: authenticate both systems, choose the objects to sync (such as Amazon RDS's Views and Columns), map fields visually, and changes propagate both ways in milliseconds — no code required.
On the Cloudera Data Platform side: Partitions, Object store / HDFS files, Databases, Hive tables, plus custom fields where Cloudera Data Platform exposes them. On the Amazon RDS side: Read Replicas, Stored Procedures, Databases, Schemas. 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 Amazon RDS and Cloudera Data Platform: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Cloudera Data Platform and keep Amazon RDS focused on its operational workload.
Amazon RDS: SQL wire protocol of the chosen engine (PostgreSQL, MySQL, MariaDB, SQL Server, Oracle). Authentication: Database credentials over SSL/TLS, or IAM database authentication on supported engines. 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. 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. Amazon RDS: RDS is a managed hosting layer, not a separate API: clients connect with standard engine drivers at the instance endpoint. Stacksync's field mapping accounts for these differences between Amazon RDS and Cloudera Data Platform without custom code.
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 Amazon RDS and Cloudera Data Platform.