Two-way sync
Changes in DuckDB or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Keep DuckDB 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.
Operational databases and analytical warehouses want the same data at different moments. Analysts want DuckDB's rows in Google Cloud 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 DuckDB where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in DuckDB sync into Google Cloud Platform in real time, and result tables in Google Cloud Platform sync back into DuckDB, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Google Cloud Platform and keep DuckDB focused on its operational workload.
Rows from DuckDB land in Google Cloud Platform as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Google Cloud Platform sync into DuckDB, 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.
| DuckDB objects | Google Cloud Platform objects | |
|---|---|---|
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Pub/Sub topics Event streams used to move change events between systems in near real time. | |
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Firestore documents Document data read and written through the Firestore API for app-facing syncs. | |
| Schemas Namespaces within a database used to organize tables in sync outputs. | Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. | |
| Tables Columnar tables created via SQL; the destination for materialized sync data. | BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. | |
| Views SQL views used to shape or filter data for downstream consumers. | BigQuery tables The primary analytics destination, written through load jobs or the Storage Write API and queried with SQL. | |
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–Google Cloud Platform connection.
Changes in DuckDB or Google Cloud Platform instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever DuckDB 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 DuckDB or Google Cloud Platform record.
Track your DuckDB ⇄ Google Cloud Platform sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between DuckDB 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 DuckDB 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 DuckDB 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 DuckDB and Google Cloud Platform: authenticate both systems, choose the objects to sync (such as DuckDB's Attached databases and Database files), map fields visually, and changes propagate both ways in milliseconds — no code required.
Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
Common patterns for DuckDB and Google Cloud Platform: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Google Cloud Platform and keep DuckDB focused on its operational workload.
DuckDB: In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default. Authentication: None built in; access control is file-system level (MotherDuck adds token auth for its hosted service). 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.
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. DuckDB: DuckDB runs in-process like SQLite; there is no server, so integrations embed the engine or operate on the single-file databases it produces. Stacksync's field mapping accounts for these differences between DuckDB 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 DuckDB and Google Cloud Platform records are not retained after a sync operation.
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 DuckDB and Google Cloud Platform.