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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
Firebolt connector details
The Firebolt materialization connector loads data from Estuary collections into Firebolt FACT or DIMENSION tables using a secure, high-performance pipeline. It stages JSON documents in Amazon S3, then leverages Firebolt’s external table mechanism to efficiently ingest and query data.
- Optimized data delivery: Writes Flow collection updates to Firebolt via S3-backed external tables for minimal latency
- Delta-based materialization: Operates in delta updates mode, perfectly suited for Firebolt’s insert-only architecture
- Seamless integration: Automatically maps Flow schemas to Firebolt FACT or DIMENSION tables
- Secure configuration: Supports IAM-based authentication for private S3 buckets
- Scalable performance: Designed to handle large-scale analytical workloads with Firebolt engines
- Enterprise-ready: Works seamlessly in Estuary’s Private and BYOC environments for full data control
💡 Tip: Use this connector to power ultra-fast analytics by streaming real-time Flow data into Firebolt, ideal for dashboards, event logs, and time-series reporting.
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 Firebolt 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 Firebolt insights always reflect the latest data by connecting your databases to Firebolt with change data capture.
- Or connect critical SaaS apps to Firebolt with real-time data pipelines.
Don't see a connector?Request and our team will get back to you in 24 hours
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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