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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
Looker connector details
Estuary’s Looker connector captures metadata and configuration data from Looker via the Looker API, allowing you to analyze dashboards, models, and user permissions in Flow collections. It provides scheduled syncs of Looker assets to support governance, auditing, and analytics visibility.
- Captures dashboards, folders, users, roles, and LookML models
- Uses Looker API credentials (Client ID and Secret) for authentication
- Supports configurable sync intervals for periodic updates
- Ideal for metadata management and analytics observability
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 from Looker 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 Looker insights always reflect the latest data by connecting your databases to Looker with change data capture.
- Or connect critical SaaS apps to Looker 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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