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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



SingleStore Dekaf connector details
The SingleStore (Dekaf) connector streams Flow collections as Kafka-compatible messages that can be consumed directly by SingleStore pipelines. It enables real-time data ingestion from Estuary into SingleStore’s distributed SQL engine for hybrid transactional and analytical workloads.
- Real-time delivery: Streams collection updates to SingleStore pipelines over Kafka in Avro format.
- High-performance integration: Leverages SingleStore’s native ingestion pipeline for low-latency, scalable data flow.
- Simple authentication: Uses a configurable auth token as both the Kafka and Schema Registry credential.
- Flexible configuration: Each Flow collection is published as a separate Kafka topic for easy mapping.
- Deletion handling: Supports both standard Kafka-style deletes and CDC deletion modes for downstream processing.
- Quick setup: Define a pipeline in SingleStore with the
LOAD DATA KAFKAcommand and start ingesting immediately.
💡 Tip: Use ReplacingMergeTree or similar table engines in SingleStore when handling CDC deletions to maintain accurate, up-to-date data states across real-time pipelines.


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 SingleStore Dekaf 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 SingleStore Dekaf insights always reflect the latest data by connecting your databases to SingleStore Dekaf with change data capture.
- Or connect critical SaaS apps to SingleStore Dekaf 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 |

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