Two-way sync
Changes in Cloudera Data Platform or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Keep Cloudera Data Platform and Google Cloud 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.
Companies end up with two warehouses for practical reasons: a migration in progress, teams that standardized on different platforms, an acquisition, or tools that only connect to one of them. The result is the same dataset maintained twice, with duplicated pipelines and numbers that almost match.
Stacksync syncs tables between Cloudera Data Platform and Google Cloud Platform continuously, in either or both directions. Rows changed on one platform appear on the other within seconds, with schema and type mapping handled, so both warehouses answer questions with the same data.
When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
Mirror the datasets a BI tool, notebook, or application needs onto the platform it can actually reach.
Where different teams run different warehouses, sync the curated tables both rely on so their metrics agree by construction.
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 Platform objects | |
|---|---|---|
| Partitions Table partitions (often by date) that incremental extraction jobs use to scope reads. | BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. | |
| Object store / HDFS files Underlying Parquet or ORC files on HDFS or cloud storage backing the tables. | Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. | |
| Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Cloud Storage objects Staging area for file-based bulk loads into BigQuery and other services. | |
| Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | Pub/Sub topics Event streams used to move change events between systems in near real time. | |
| Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Firestore documents Document data read and written through the Firestore API for app-facing syncs. | |
| Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cloudera Data Platform–Google Cloud Platform connection.
Changes in Cloudera Data Platform or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Cloudera Data Platform or Google Cloud 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 Cloudera Data Platform or Google Cloud Platform record.
Track your Cloudera Data Platform ⇄ Google Cloud Platform 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 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 Cloudera Data Platform and Google Cloud 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 Cloudera Data Platform and Google Cloud 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 Cloudera Data Platform and Google Cloud Platform: 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.
Common patterns for Cloudera Data Platform and Google Cloud Platform: Migration without a big bang; Serve tools that only connect to one platform; Shared datasets across teams. When one platform is replacing the other, keep tables mirrored while workloads move over gradually, and cut over with nothing to backfill.
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. Google Cloud Platform: Per-service REST and gRPC APIs; BigQuery speaks SQL and Cloud SQL exposes standard database wire protocols. Authentication: IAM service accounts with OAuth 2.0 tokens. Stacksync manages authentication, retries, and rate limits on both sides.
Cloudera Data Platform: Tables can live in multiple storage engines with different update semantics: Kudu and Iceberg tables support row-level updates, while classic Hive tables are append-oriented. Google Cloud Platform: Cloud SQL Postgres and MySQL expose log-based CDC (logical replication and binlog), which Datastream and external sync tools consume for real-time replication. Stacksync's field mapping accounts for these differences between Cloudera Data Platform and Google Cloud 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 Cloudera Data Platform and Google Cloud Platform 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 Platform connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Cloudera Data Platform–Google Cloud Platform integration in-house.
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 Platform.