Two-way sync
Changes in AWS Aurora MySQL or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora MySQL 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 AWS Aurora MySQL'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 AWS Aurora MySQL where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in AWS Aurora MySQL sync into Cloudera Data Platform in real time, and result tables in Cloudera Data Platform sync back into AWS Aurora MySQL, 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 AWS Aurora MySQL focused on its operational workload.
Rows from AWS Aurora MySQL 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 AWS Aurora MySQL, 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.
| AWS Aurora MySQL objects | Cloudera Data Platform objects | |
|---|---|---|
| Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. | Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | |
| Databases (schemas) Logical namespaces that scope which tables a sync connection can see. | Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. | |
| Tables The primary sync unit; each table maps one-to-one to a table or object in the paired system. | Views SQL views that can present curated, sync-ready projections of raw lake data. | |
| Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | |
| Columns MySQL data types are mapped to the paired system's field types during schema setup. | Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. | |
| Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–Cloudera Data Platform connection.
Changes in AWS Aurora MySQL or Cloudera Data Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora MySQL 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 AWS Aurora MySQL or Cloudera Data Platform record.
Track your AWS Aurora MySQL ⇄ Cloudera Data Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL 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 AWS Aurora MySQL 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 AWS Aurora MySQL 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 AWS Aurora MySQL and Cloudera Data Platform: authenticate both systems, choose the objects to sync (such as AWS Aurora MySQL's Stored procedures and triggers and Databases (schemas)), map fields visually, and changes propagate both ways in milliseconds — no code required.
AWS Aurora MySQL: SQL wire protocol (MySQL-compatible), standard MySQL drivers and JDBC. Authentication: Database credentials, optionally AWS IAM database authentication, over TLS. 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: Access is commonly brokered by Apache Knox and secured with Kerberos or LDAP, which integration tooling must support. AWS Aurora MySQL: Aurora MySQL is wire-compatible with MySQL, so any standard MySQL driver, ORM, or CDC tooling works without modification. Stacksync's field mapping accounts for these differences between AWS Aurora MySQL and Cloudera Data Platform 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 AWS Aurora MySQL and Cloudera Data Platform records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed AWS Aurora MySQL and Cloudera Data Platform connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom AWS Aurora MySQL–Cloudera Data Platform integration in-house.
Yes — Stacksync ships production-grade connectors for both AWS Aurora MySQL and Cloudera Data Platform. 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 AWS Aurora MySQL and Cloudera Data Platform.