Stream data from BigQuery to SingleStore
Move data from BigQuery to SingleStore in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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- 200+Connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate BigQuery with SingleStore in 3 simple steps
- 1
Connect BigQuery as your data source
Set up a source connector for BigQuery in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
- 2
Configure SingleStore as your destination connector
Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to SingleStore.
- 3
Deploy and Monitor Your End-to-End Data Pipeline
Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

BigQuery connector details
The BigQuery Batch connector captures data from your BigQuery datasets into Estuary collections by periodically running SQL queries and translating the results into JSON documents. It’s ideal for analytical workloads or datasets that don’t require continuous change tracking.
- Periodically executes queries from BigQuery tables or views and loads results into Estuary collections
- Supports cursor-based incremental updates for efficient polling and reduced reprocessing
- Customizable polling intervals (default: every 24 hours) for flexible scheduling
- Uses a Google Cloud Service Account with BigQuery User and Data Viewer roles for secure access
- Works seamlessly within Estuary’s Private and BYOC environments for compliance and governance
💡 Tip: Specify a timestamp or monotonically increasing ID column as your cursor to reduce data volume and capture only new or updated records efficiently.

SingleStore connector details
The SingleStore materialization connector in Estuary delivers data from Estuary collections directly into tables in a SingleStore database. It supports continuous materialization from real-time or batch pipelines, using standard merge-based updates by default with optional delta updates for applicable workloads.
- Materializes Estuary collections directly into SingleStore tables
- Standard merge-based updates by default to keep destination records synchronized
- Optional delta updates for workloads where changes should be applied incrementally
- Automatic table creation for configured materialization bindings
- Custom SQL after table creation for additional table-level configuration
- Configurable destination table names for individual bindings
- SSL/TLS connection support, including certificate and hostname verification
- Configurable timezone handling for datetime columns
- Username and password authentication
- Support for SingleStoreDB Cloud, including SSL-secured connections
- Option to exclude the root Flow document from standard updates for advanced use cases
Each materialization binding maps an Estuary collection to a SingleStore table. The connector creates the destination table when needed, and you can optionally run additional SQL after table creation for further configuration.
For SingleStoreDB Cloud, SSL is required. Estuary supports several SSL modes, including verify_ca and verify_identity, with support for supplying the SingleStore server CA certificate.

See how Recart uses SingleStore
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Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

BigQuery to SingleStore pricing estimate
Estimated monthly cost to move 800 GB from BigQuery to SingleStore is approximately $1,000.
Data moved
Choose how much data you want to move from BigQuery to SingleStore each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.



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Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this BigQuery to SingleStore integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
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