Two-way sync
Changes in BigQuery or Teradata Vantage instantly reflect in both systems. No stale data, no manual imports.
Keep BigQuery and Teradata Vantage 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 BigQuery and Teradata Vantage 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.
| BigQuery objects | Teradata Vantage objects | How this pairing syncs | |
|---|---|---|---|
| Tables The syncable unit: only tables can be synced per the Stacksync docs. | Tables The primary sync unit for both extraction and loading. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Projects Connection scope: the service account grants access per project. | Columns Teradata SQL types mapped to the paired system's field types during sync. | Projects is specific to BigQuery and Columns to Teradata Vantage — each maps to any object or custom field on the other side. | |
| Partitioned tables Synced like regular tables; partition columns map to target fields. | Databases Hierarchical containers that own tables and space allocations. | Partitioned tables is specific to BigQuery and Databases to Teradata Vantage — each maps to any object or custom field on the other side. | |
| Clustered tables Supported; clustering is transparent to the sync. | Views The conventional access layer in Teradata shops; syncs often read views rather than base tables. | Clustered tables is specific to BigQuery and Views to Teradata Vantage — each maps to any object or custom field on the other side. | |
| Datasets Organizational container — you pick which dataset’s tables to sync. | Macros Stored parameterized SQL that encapsulates repeatable reads. | Datasets is specific to BigQuery and Macros to Teradata Vantage — each maps to any object or custom field on the other side. |
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.
DetectionChanges in BigQuery are captured at the source via change data capture — no polling loop against its API. Real-time notification service deployed into your Google Cloud project: Eventarc ("a notification service that enables real-time updates to happen").
DeliveryEach detected change is applied to Teradata Vantage as a row-level write, with types converted between the two schemas.
DetectionStacksync polls Teradata Vantage for changes on an incremental schedule, reading only records changed since the previous pass. Query-based polling.
DeliveryEach detected change is applied to BigQuery as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every BigQuery–Teradata Vantage connection.
Changes in BigQuery or Teradata Vantage instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever BigQuery or Teradata Vantage 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 Teradata Vantage record.
Track your BigQuery ⇄ Teradata Vantage sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between BigQuery and Teradata Vantage.
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 Teradata Vantage 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 Teradata Vantage 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 Teradata Vantage: authenticate both systems, choose the objects to sync (such as BigQuery's Tables and Projects), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for BigQuery and Teradata Vantage: 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.
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. Teradata Vantage: ANSI SQL over JDBC/ODBC/.NET drivers; REST access available through Teradata's query service. Authentication: Database credentials; LDAP or Kerberos in enterprise deployments. Stacksync manages authentication, retries, and rate limits on both sides.
BigQuery: Google quota of 1,500 table modifications per BigQuery table per day (DELETE, INSERT, MERGE, TRUNCATE TABLE, UPDATE). Teradata Vantage: Bulk data movement is conventionally done through utilities such as Teradata Parallel Transporter rather than row-by-row inserts, which shapes how loads should be batched. Stacksync's field mapping accounts for these differences between BigQuery and Teradata Vantage 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 Teradata Vantage records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed BigQuery and Teradata Vantage connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom BigQuery–Teradata Vantage 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 475 integrations available for BigQuery and Teradata Vantage.