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Continously ingest and deliver both streaming and batch change data from 100s of sources using Estuary's custom no-code connectors.
- <100ms Data pipelines
- 100+ Connectors
- 2-5x less than batch ELT
Google Sheets connector details
The Google Sheets materialization connector continuously syncs data from Estuary Flow collections into Google Sheets, making real-time data accessible for collaboration, analysis, and reporting in a familiar spreadsheet interface.
- Real-time sync: Streams updates from Flow collections directly into Google Sheets in near real time
- Simple setup: Authenticate quickly using OAuth in the Flow web app, or use a Service Account JSON key for manual configuration
- Per-sheet mapping: Materialize multiple Flow collections into separate sheets within the same spreadsheet
- Automatic state tracking: Each sheet includes an internal tracking column to ensure data consistency
- Cell limit awareness: Supports up to 1 million cells per sheet; larger datasets should be summarized or aggregated first
💡 Tip: Use Google Sheets materialization for lightweight reporting, team dashboards, or quick data validation workflows. For larger-scale analytics, consider exporting to BigQuery or S3.
HIGH THROUGHPUT
Distributed event-driven architecture enable boundless scaling with exactly-once semantics.
DURABLE REPLICATION
Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.
REAL-TIME INGESTION
Capture and relay every insert, update, and delete in milliseconds.
Real-timehigh throughput
Point a connector and replicate changes to Google Sheets in <100ms. Leverage high-availability, high-throughput Change Data Capture.Or choose from 100s of batch and real-time connectors to move and transform data using ELT and ETL.
- Ensure your Google Sheets insights always reflect the latest data by connecting your databases to Google Sheets with change data capture.
- Or connect critical SaaS apps to Google Sheets with real-time data pipelines.
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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.
Feature Comparison
| Estuary | Batch ELT/ETL | DIY Python | KAFKA | |
|---|---|---|---|---|
| Price | $ | $$-$$$$ | $-$$$$ | $-$$$$ |
| Speed | <100ms | 5min+ | Varies | <100ms |
| Ease | Analysts can manage | Analysts can manage | Data Engineer | Senior Data Engineer |
| Scale |
Deliver real-time and batch data from DBs, SaaS, APIs, and more
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