Two-way sync
Changes in Databricks or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Keep Databricks 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 Databricks 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.
Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
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.
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 Cloud Platform objects | |
|---|---|---|
| Change Data Feed Row-level change records on Delta tables that drive incremental reads. | BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. | |
| Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. | |
| Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. | |
| Delta Tables The primary read and write target; operational data lands here as managed or external tables. | Cloud Storage objects Staging area for file-based bulk loads into BigQuery and other services. | |
| Views Curated read-only projections used as sync sources for downstream tools. | Pub/Sub topics Event streams used to move change events between systems in near real time. | |
| Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Firestore documents Document data read and written through the Firestore API for app-facing syncs. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Databricks–Google Cloud Platform connection.
Changes in Databricks or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Databricks 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 Databricks or Google Cloud Platform record.
Track your Databricks ⇄ Google Cloud Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Databricks 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 Databricks 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 Databricks 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 Databricks and Google Cloud Platform: authenticate both systems, choose the objects to sync (such as Databricks's Change Data Feed and Catalogs), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Databricks and Google Cloud Platform: Consolidation after M&A; Migration without a big bang; Serve tools that only connect to one platform. Bring the acquired company's warehouse data across continuously instead of through one-off dumps.
Databricks: 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. 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.
Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Google Cloud Platform: BigQuery is append-oriented: row mutations go through DML or the Storage Write API, and streamed rows pass through a buffer before some operations can touch them. Stacksync's field mapping accounts for these differences between Databricks 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 Databricks 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 Databricks and Google Cloud Platform connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Databricks–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 Databricks and Google Cloud Platform.