Two-way sync
Changes in Cloudera Data Platform or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.
Keep Cloudera Data Platform and Google Cloud SQL 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 Google Cloud SQL'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 Google Cloud SQL where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Google Cloud SQL sync into Cloudera Data Platform in real time, and result tables in Cloudera Data Platform sync back into Google Cloud SQL, 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 Google Cloud SQL focused on its operational workload.
Rows from Google Cloud SQL 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 Google Cloud SQL, 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.
| Cloudera Data Platform objects | Google Cloud SQL objects | |
|---|---|---|
| Views SQL views that can present curated, sync-ready projections of raw lake data. | Databases Scope the tables included in a sync configuration. | |
| Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | Schemas Namespace tables in PostgreSQL and SQL Server instances. | |
| Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. | Tables Mapped directly to sync targets; schema changes can be propagated. | |
| Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Rows Read and written by primary key during each sync cycle. | |
| Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | Views Read-only sources for shaping data before syncing it out. | |
| Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Transaction logs MySQL binlog or PostgreSQL WAL, the source for log-based change capture. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cloudera Data Platform–Google Cloud SQL connection.
Changes in Cloudera Data Platform or Google Cloud SQL instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Cloudera Data Platform or Google Cloud SQL 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 Google Cloud SQL record.
Track your Cloudera Data Platform ⇄ Google Cloud SQL sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Cloudera Data Platform and Google Cloud SQL.
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 Google Cloud SQL 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 Google Cloud SQL 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 Google Cloud SQL: authenticate both systems, choose the objects to sync (such as Cloudera Data Platform's Views and Partitions), map fields visually, and changes propagate both ways in milliseconds — no code required.
Cloudera Data Platform: Access is commonly brokered by Apache Knox and secured with Kerberos or LDAP, which integration tooling must support. Google Cloud SQL: Change capture is engine-specific: binlog replication on MySQL, logical replication slots on PostgreSQL, and change tracking or CDC features on SQL Server. Stacksync's field mapping accounts for these differences between Cloudera Data Platform and Google Cloud SQL 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 Google Cloud SQL 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 Google Cloud SQL connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Cloudera Data Platform–Google Cloud SQL integration in-house.
Yes — Stacksync ships production-grade connectors for both Cloudera Data Platform and Google Cloud SQL. 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 Google Cloud SQL: Engine-dependent log-based CDC: MySQL binlog, PostgreSQL logical replication, SQL Server change tracking; polling as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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 Google Cloud SQL.