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Sign inReal-Time Change Data Capture (CDC)
Stream database changes as they happen. Etlworks enables low-latency, high-volume CDC across any source and destination: relational databases, APIs, cloud warehouses, and more.
Why it matters: Capturing and delivering data changes in real time helps organizations stay responsive and informed. Etlworks enables timely analytics, faster decision-making, and smoother data synchronization across systems.
Technical Details & Security
- Change Data Capture (CDC) from transaction log
- CDC Case Studies
- SOC 3 Report (SOC 2 Report available after NDA)
- Security Policies
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Why Etlworks
Real-time CDC: Capture changes from MySQL, PostgreSQL, SQL Server, Oracle, MongoDB, and more.
Reliable and Scalable: Stream from thousands of databases at once with built-in resiliency, retries, and checkpointing.
Minimal Impact: Non-intrusive agents and log-based capture ensure zero disruption to source systems.
Transform on the fly: Enrich and transform data mid-stream or downstream before loading into destinations.
Stream anywhere: Push CDC data into Snowflake, BigQuery, Redshift, file systems, message queues, databasesand more.
Trused By
How Organizations Use Etlworks for Real-Time CDC
Intertek Alchemy, a global leader in workforce training solutions, streams
CDC data in real time from over 1,500 MySQL databases into Snowflake using Etlworks. No
other platform could match the scalability and performance required.
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the case study
Tallink integrated real-time CDC with batch ETL to ensure high availability
and data accuracy across MySQL, Postgres, Oracle, APIs, and file systems. Etlworks reliably
powers critical logistics and passenger operations.
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the case study
Israel Tax Authority modernized its pipelines with Etlworks, streaming
massive volumes of data from SQL Server into Vertica with CDC. The solution met strict
government compliance requirements while improving reliability and throughput.
Read
the case study
Ambyint, a leader in AI-powered oilfield optimization, uses Etlworks to
stream CDC from multiple MongoDB databases to Snowflake. Combined with real-time device data
ingestion via MQTT, this enables immediate insight and decision-making.
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the case study