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Data warehouse ⇄ Database

Databricks to Google AlloyDB integration — real-time, two-way sync

Keep Databricks 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Databricks and Google AlloyDB

Connect Google AlloyDB and Databricks 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 Databricks, 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 Databricks in real time, and result tables in Databricks sync back into Google AlloyDB, with schema and type mapping between the two systems handled for you.

Common use cases

  • Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
  • Consolidate SaaS data into AlloyDB and serve analytics from its columnar engine without a separate OLAP store.
  • Migrate workloads from self-managed Postgres while keeping existing syncs pointed at a compatible endpoint.

Offload heavy reads

Point analytical queries at the synced copy in Databricks and keep Google AlloyDB focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Google AlloyDB land in Databricks as they change, replacing hand-built CDC and batch extract jobs.

Serve warehouse results at database speed

Aggregates or model outputs computed in Databricks sync into Google AlloyDB, where whatever reads from that database gets them without querying the warehouse.

What you can sync between Databricks 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.

Databricks objects Google AlloyDB objects
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Databases Standard PostgreSQL databases within an AlloyDB cluster that syncs connect to.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Schemas Namespaces used to separate synced SaaS data from application tables.
Views Curated read-only projections used as sync sources for downstream tools. Tables Primary read/write target for bi-directional sync with CRMs and other systems.
Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Views Curated projections used as read-only sync sources.
Volumes Unity Catalog file storage used for staging bulk loads. Materialized Views Precomputed aggregates refreshed and synced outward on a schedule.
SQL Warehouses The compute endpoint a sync connects to for query execution. Indexes Keep sync key lookups fast on high-volume tables.
What ships with Databricks ⇄ Google AlloyDB

Connect Databricks and Google AlloyDB for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Google AlloyDB connection.

Real-time

Two-way sync

Changes in Databricks or Google AlloyDB instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks 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 Databricks or Google AlloyDB record.

Observability

Monitoring

Track your Databricks ⇄ 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 Databricks and Google AlloyDB.

How the Databricks and Google AlloyDB connectors work

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace 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 Databricks 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.

  1. 01

    Connect your apps

    Authenticate Databricks 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Databricks connected
    Google AlloyDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Databricks ⇄ Google AlloyDB
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Databricks Google AlloyDB
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and Google AlloyDB integration FAQ

SECURITY

Security teams love 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.

Learn more about security
SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Databricks and Google AlloyDB.

Popular · 8 of 386
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