Real-time
Two-way sync
Changes in Google Cloud Platform or OpenSearch instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
Google Cloud Platform to OpenSearch integration — real-time, two-way sync
Keep Google Cloud Platform and OpenSearch in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect Google Cloud Platform and OpenSearch
Connect OpenSearch and Google Cloud 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 OpenSearch'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 OpenSearch where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in OpenSearch sync into Google Cloud Platform in real time, and result tables in Google Cloud Platform sync back into OpenSearch, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Publish change events to Pub/Sub so downstream services react to record updates as they happen.
- 02 Sync product catalogs from an ERP or database into the indexes that back storefront search.
- 03 Keep Postgres as the source of truth while mirroring rows to OpenSearch for full-text and vector queries.
Common sync patterns
Fresh analytics without loading windows
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Offload heavy reads
Point analytical queries at the synced copy in Google Cloud Platform and keep OpenSearch focused on its operational workload.
Operational data in the warehouse, minus the pipeline
Rows from OpenSearch land in Google Cloud Platform as they change, replacing hand-built CDC and batch extract jobs.
What you can sync between Google Cloud Platform and OpenSearch
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.
| Google Cloud Platform objects | OpenSearch objects | How this pairing syncs | |
|---|---|---|---|
| Cloud SQL databases Managed Postgres, MySQL, and SQL Server instances synced like ordinary relational databases. | Ingest pipelines Server-side processors that transform documents as they are written | Cloud SQL databases is specific to Google Cloud Platform and Ingest pipelines to OpenSearch — each maps to any object or custom field on the other side. | |
| Cloud Storage objects Staging area for file-based bulk loads into BigQuery and other services. | Data streams Append-oriented time-series storage for logs and events pushed from source systems | Cloud Storage objects is specific to Google Cloud Platform and Data streams to OpenSearch — each maps to any object or custom field on the other side. | |
| Pub/Sub topics Event streams used to move change events between systems in near real time. | Snapshots Backup artifacts, relevant when reseeding an index from a repository | Pub/Sub topics is specific to Google Cloud Platform and Snapshots to OpenSearch — each maps to any object or custom field on the other side. | |
| Firestore documents Document data read and written through the Firestore API for app-facing syncs. | Indexes The core container; synced records land in indexes with defined mappings | Firestore documents is specific to Google Cloud Platform and Indexes to OpenSearch — each maps to any object or custom field on the other side. | |
| Spanner tables Strongly consistent relational tables accessed via SQL for transactional workloads. | Documents JSON records written via the index and bulk APIs and read via search queries | Spanner tables is specific to Google Cloud Platform and Documents to OpenSearch — each maps to any object or custom field on the other side. | |
| BigQuery datasets Namespaces that group tables; syncs target tables within a dataset. | Index aliases Stable names over rotating indexes, used for zero-downtime reindex during backfills | BigQuery datasets is specific to Google Cloud Platform and Index aliases to OpenSearch — each maps to any object or custom field on the other side. |
How changes propagate between Google Cloud Platform and OpenSearch
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.
Google Cloud Platform OpenSearch Sub-second propagation
DetectionGoogle Cloud Platform pushes changes as they happen — webhook events backed by change data capture. Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery.
DeliveryEach detected change is written to OpenSearch through its API, with automatic retries and rate-limit backoff.
OpenSearch Google Cloud Platform Interval-based propagation
DetectionStacksync polls OpenSearch for changes on an incremental schedule, reading only records changed since the previous pass. No native change feed.
DeliveryEach detected change is applied to Google Cloud Platform as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Google Cloud Platform: Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits.
- OpenSearch: Throughput bounded by cluster sizing rather than fixed API quotas.
What ships with Google Cloud Platform ⇄ OpenSearch
Connect Google Cloud Platform and OpenSearch for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Google Cloud Platform–OpenSearch connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Google Cloud Platform or OpenSearch 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 Google Cloud Platform or OpenSearch record.
Observability
Monitoring
Track your Google Cloud Platform ⇄ OpenSearch sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Google Cloud Platform and OpenSearch.
How the Google Cloud Platform and OpenSearch connectors work
Google Cloud Platform
- Integration surface
- 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
- Change detection
- Varies by service: log-based CDC on Cloud SQL (logical replication or binlog, also via Datastream), Pub/Sub for event delivery, polling for BigQuery tables
- Capabilities
- read · write · CDC · webhooks
- Rate limits
- Quotas are set per service and per project; BigQuery, Pub/Sub, and Cloud SQL each enforce their own limits
OpenSearch
- Integration surface
- REST API over HTTP(S) with JSON payloads
- Authentication
- basic authentication with the security plugin, or AWS IAM request signing on Amazon OpenSearch Service
- Change detection
- no native change feed; reads rely on queries with scroll or point-in-time polling
- Capabilities
- read · write
- Rate limits
- throughput bounded by cluster sizing rather than fixed API quotas
How it works
How to connect Google Cloud Platform to OpenSearch — 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 Google Cloud Platform and OpenSearch with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Google Cloud Platform
connected
OpenSearch
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Google Cloud Platform and OpenSearch 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 · Google Cloud Platform ⇄ OpenSearchCustomers 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.
Google Cloud Platform OpenSearchCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Google Cloud Platform and OpenSearch integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Google Cloud Platform and OpenSearch: authenticate both systems, choose the objects to sync (such as Google Cloud Platform's Cloud SQL databases and Cloud Storage objects), map fields visually, and changes propagate both ways in milliseconds — no code required.
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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.
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Common patterns for Google Cloud Platform and OpenSearch: Fresh analytics without loading windows; Offload heavy reads; Operational data in the warehouse, minus the pipeline. Because changes stream continuously, analysts query current data instead of waiting for last night's load.
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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. OpenSearch: REST API over HTTP(S) with JSON payloads. Authentication: Basic authentication with the security plugin, or AWS IAM request signing on Amazon OpenSearch Service. Stacksync manages authentication, retries, and rate limits on both sides.
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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. OpenSearch: Amazon OpenSearch Service domains typically authenticate with IAM request signing, while self-managed clusters use the security plugin's basic auth or certificates. Stacksync's field mapping accounts for these differences between Google Cloud Platform and OpenSearch 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 Google Cloud Platform and OpenSearch records are not retained after a sync operation.
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:
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