Two-way sync
Changes in BigQuery or Redis Enterprise instantly reflect in both systems. No stale data, no manual imports.
Keep BigQuery and Redis Enterprise 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 Redis Enterprise's rows in BigQuery, 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 Redis Enterprise where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Redis Enterprise sync into BigQuery in real time, and result tables in BigQuery sync back into Redis Enterprise, with schema and type mapping between the two systems handled for you.
Aggregates or model outputs computed in BigQuery sync into Redis Enterprise, where whatever reads from that database gets them without querying the warehouse.
Because changes stream continuously, analysts query current data instead of waiting for last night's load.
Point analytical queries at the synced copy in BigQuery and keep Redis Enterprise focused on its operational workload.
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.
| BigQuery objects | Redis Enterprise objects | |
|---|---|---|
| Clustered tables Supported; clustering is transparent to the sync. | Hashes Field-value maps that commonly hold one synced row per hash, keyed by record ID. | |
| Datasets Organizational container — you pick which dataset’s tables to sync. | JSON documents Native JSON storage (RedisJSON) for nested records synced from APIs or document stores. | |
| Projects Connection scope: the service account grants access per project. | Sets Unordered unique-member collections used for membership checks like segment or ID lists. | |
| Tables The syncable unit: only tables can be synced per the Stacksync docs. | Sorted Sets Score-ordered collections used for rankings, priority queues, and time-ordered indexes. | |
| Partitioned tables Synced like regular tables; partition columns map to target fields. | Lists Ordered sequences often used as lightweight queues fed by sync events. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–Redis Enterprise connection.
Changes in BigQuery or Redis Enterprise instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever BigQuery or Redis Enterprise data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single BigQuery or Redis Enterprise record.
Track your BigQuery ⇄ Redis Enterprise sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between BigQuery and Redis Enterprise.
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 BigQuery and Redis Enterprise 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 BigQuery and Redis Enterprise 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 BigQuery and Redis Enterprise: authenticate both systems, choose the objects to sync (such as BigQuery's Clustered tables and Datasets), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for BigQuery and Redis Enterprise: Serve warehouse results at database speed; Fresh analytics without loading windows; Offload heavy reads. Aggregates or model outputs computed in BigQuery sync into Redis Enterprise, where whatever reads from that database gets them without querying the warehouse.
BigQuery: GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs. Authentication: Google Cloud service account: create a dedicated service account, grant roles (BigQuery Data Editor, BigQuery Job User, Cloud Functions Service Agent, Cloud Run Developer, Eventarc Event Receiver. Redis Enterprise: Redis wire protocol (RESP) via client libraries; separate REST API for cluster management. Authentication: Password or ACL-based credentials, typically over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
BigQuery: The Storage Write API supports high-throughput streaming ingestion, which suits continuous sync loads better than legacy streaming inserts. Redis Enterprise: Keyspace notifications are delivered over pub/sub with no replay, so reliable change capture usually pairs them with Streams or periodic reconciliation. Stacksync's field mapping accounts for these differences between BigQuery and Redis Enterprise 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 BigQuery and Redis Enterprise records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed BigQuery and Redis Enterprise connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom BigQuery–Redis Enterprise 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 BigQuery and Redis Enterprise.