Real-time
Two-way sync
Changes in Cloudera Data Platform or Google AlloyDB instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Cloudera Data Platform to Google AlloyDB integration — real-time, two-way sync
Keep Cloudera Data Platform and Google AlloyDB in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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Why teams connect Cloudera Data Platform and Google AlloyDB
Connect Google AlloyDB and Cloudera Data Platform with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Google AlloyDB'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 AlloyDB 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 AlloyDB sync into Cloudera Data Platform in real time, and result tables in Cloudera Data Platform sync back into Google AlloyDB, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Consolidate tables from on-prem and cloud CDP environments into a single cloud warehouse target.
- 02 Sync curated CDP tables into an operational Postgres so applications query a low-latency copy instead of hitting the cluster.
- 03 Consolidate SaaS data into AlloyDB and serve analytics from its columnar engine without a separate OLAP store.
- 04 Migrate workloads from self-managed Postgres while keeping existing syncs pointed at a compatible endpoint.
Common sync patterns
Operational data in the warehouse, minus the pipeline
Rows from Google AlloyDB land in Cloudera Data Platform as they change, replacing hand-built CDC and batch extract jobs.
Serve warehouse results at database speed
Aggregates or model outputs computed in Cloudera Data Platform sync into Google AlloyDB, where whatever reads from that database gets them without querying the warehouse.
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
What you can sync between Cloudera Data Platform and Google AlloyDB
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 AlloyDB objects | How this pairing syncs | |
|---|---|---|---|
| Databases Logical namespaces in the shared Hive Metastore that group tables for access control and syncs. | Databases Standard PostgreSQL databases within an AlloyDB cluster that syncs connect to. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Views SQL views that can present curated, sync-ready projections of raw lake data. | Views Curated projections used as read-only sync sources. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Hive tables Warehouse tables queried over JDBC/ODBC; classic managed tables are append-oriented. | Schemas Namespaces used to separate synced SaaS data from application tables. | Hive tables is specific to Cloudera Data Platform and Schemas to Google AlloyDB — each maps to any object or custom field on the other side. | |
| Impala tables The same metastore tables served through Impala for lower-latency SQL reads. | Tables Primary read/write target for bi-directional sync with CRMs and other systems. | Impala tables is specific to Cloudera Data Platform and Tables to Google AlloyDB — each maps to any object or custom field on the other side. | |
| Kudu tables Storage engine tables that support row-level inserts, updates, and deletes. | Materialized Views Precomputed aggregates refreshed and synced outward on a schedule. | Kudu tables is specific to Cloudera Data Platform and Materialized Views to Google AlloyDB — each maps to any object or custom field on the other side. | |
| Iceberg tables Open table format tables in newer CDP versions, with snapshot metadata usable for incremental reads. | Indexes Keep sync key lookups fast on high-volume tables. | Iceberg tables is specific to Cloudera Data Platform and Indexes to Google AlloyDB — each maps to any object or custom field on the other side. |
How changes propagate between Cloudera Data Platform and Google AlloyDB
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
Cloudera Data Platform Google AlloyDB Interval-based propagation
DetectionStacksync polls Cloudera Data Platform for changes on an incremental schedule, reading only records changed since the previous pass. Polling via SQL on timestamp or partition columns.
DeliveryEach detected change is applied to Google AlloyDB as a row-level write, with types converted between the two schemas.
Google AlloyDB Cloudera Data Platform Sub-second propagation
DetectionChanges in Google AlloyDB are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication.
DeliveryEach detected change is applied to Cloudera Data Platform as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Cloudera Data Platform: Constrained by cluster capacity and admission control rather than API rate limits.
- Google AlloyDB: No API-style rate limits; throughput is bounded by instance size.
What ships with Cloudera Data Platform ⇄ Google AlloyDB
Connect Cloudera Data Platform and Google AlloyDB for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Cloudera Data Platform–Google AlloyDB connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Cloudera Data Platform or Google AlloyDB data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
At scale
Event queues
Handle millions of events per minute without losing a single Cloudera Data Platform or Google AlloyDB record.
Observability
Monitoring
Track your Cloudera Data Platform ⇄ Google AlloyDB sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Cloudera Data Platform and Google AlloyDB.
How the Cloudera Data Platform and Google AlloyDB connectors work
Cloudera Data Platform
- Integration surface
- 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
- Change detection
- Polling via SQL on timestamp or partition columns; no consumer-facing change feed
- Capabilities
- read · write
- Rate limits
- Constrained by cluster capacity and admission control rather than API rate limits
Google AlloyDB
- Integration surface
- SQL wire protocol (PostgreSQL-compatible), with connectivity through the AlloyDB Auth Proxy or private IP
- Authentication
- Database credentials or IAM database authentication
- Change detection
- Log-based CDC via PostgreSQL logical replication; polling on timestamp columns as a fallback
- Capabilities
- read · write · CDC
- Rate limits
- No API-style rate limits; throughput is bounded by instance size
How it works
How to connect Cloudera Data Platform to Google AlloyDB — three steps, no code
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.
- 01
Connect your apps
Authenticate Cloudera Data Platform and Google AlloyDB with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Cloudera Data Platform
connected
Google AlloyDB
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Cloudera Data Platform and Google AlloyDB 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.
objects · Cloudera Data Platform ⇄ Google AlloyDBCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Cloudera Data Platform Google AlloyDBCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Cloudera Data Platform and Google AlloyDB integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Cloudera Data Platform and Google AlloyDB: authenticate both systems, choose the objects to sync (such as Cloudera Data Platform's Databases and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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. Google AlloyDB: IAM database authentication lets connections use Google Cloud identities instead of static passwords. Stacksync's field mapping accounts for these differences between Cloudera Data Platform and Google AlloyDB without custom code.
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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 AlloyDB records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Cloudera Data Platform and Google AlloyDB connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Cloudera Data Platform–Google AlloyDB integration in-house.
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Yes — Stacksync ships production-grade connectors for both Cloudera Data Platform and Google AlloyDB. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Cloudera Data Platform: Polling via SQL on timestamp or partition columns; no consumer-facing change feed. On Google AlloyDB: Log-based CDC via PostgreSQL logical replication; polling on timestamp columns as a fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
SECURITY
Security teams trust Stacksync
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Related integrations
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