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REAL-TIME ETL & CDC

Stream into SingleStore Dekaf with your free account

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
01. Select a source02. Transform in-flight03. Deliver to SingleStore Dekaf
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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 KAFKA command 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.

For more details about the SingleStore Dekaf connector, check out the documentation page.

How to connect your data source to SingleStore Dekaf in 3 easy steps

1

Connect your data source

Select from more than 100 supported databases and SaaS platforms including PostgreSQL, MySQL, SQL Server, MongoDB, and Kafka.

2

Prepare and transform your data

Apply transformations and schema mapping as data moves whether you are streaming in real time or loading in batches.

3

Sync to SingleStore Dekaf

Continuously or periodically deliver data into your destination with support for change data capture and reliable delivery for accurate insights.

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Trusted by data teams worldwide

All data connections are fully encrypted in transit and at rest. Estuary also supports private cloud and BYOC deployments for maximum security and compliance.

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HIGH THROUGHPUT

Distributed event-driven architecture enable boundless scaling with exactly-once semantics.

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DURABLE REPLICATION

Cloud storage backed CDC w/ heart beats ensures reliability, even if your destination is down.

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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.

See how you can integrate any source with SingleStore Dekaf:

Details

or choose from these popular data sources:

PostgreSQL logo
PostgreSQL
MySQL logo
MySQL
SQL Server logo
SQL Server
MongoDB logo
MongoDB
Apache Kafka logo
Apache Kafka
BigQuery logo
BigQuery
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Snowflake Data Cloud

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Pipelines as fast as Kafka, easy as managed ELT/ETL, cheaper than building it.

Feature Comparison

EstuaryBatch ELT/ETLDIY PythonKafka
Price$$$-$$$$$-$$$$$-$$$$
Speed<100ms5min+Varies<100ms
EaseAnalysts can manageAnalysts can manageData EngineerSenior Data Engineer
Scale
Maintenance EffortLowMediumHighHigh
Detailed Comparison

Deliver real-time and batch data from DBs, SaaS, APIs, and more

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Popular sources/destinations you can sync your data with

Choose from more than 100 supported databases and SaaS applications. Click any source/destination below to open the integration guide and learn how to sync your data in real time or batches.