Consolidate Streaming Data with
Change Data Capture (CDC) Ingestion

The powerful alternative for continuous data replication and the gateway to streaming

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Stream Change Data Capture From Your Data Sources
into Your Data Lake and Warehouse in Real-Time

Change Data Capture Ingestion
& Replication in One Platform

Execute both Change Data Capture
Replication and CDC Event Processing
with a single platform

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No Code-UI

Execute complex flows, bulk
replicate, adjust targets and
sources with the click of your
mouse - not complex coding.

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Robust Transformations
for In-Flight Data

Transform, enrich and correlate raw
CDC events in-flight. If you need
batch ingestion too, we've got
you covered.

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With Equalum, Teams Can...

Leverage a Fully Optimized, Native
Change Data Capture Ingestion & Replication

Not all CDC solutions are created equal. Leverage a native Change Data Capture solution that does not compromise on CDC replication best practices, while also delivering transformation in-motion & even processing.

Why This Matters
Handle unparalleled scale, executed on
Apache Spark & Kafka

Power Change Data Capture ingestion and replication with a fully managed Apache Kafka & Spark, the best modern pipeline architecture available to handle unlimited scale.

Trust a fully managed, enterprise grade
CDC streaming solution

Maximum productivity with minimum maintenance and administration. Fully managed orchestration, no coding UI enterprise grade monitoring, alerting, security, data ops and more.


The Benefits of Modern, Multi-Modal Change Data Capture

Change data capture is the lowest-impact way of asynchronously capturing database changes. But legacy CDC solutions come with a number of limitations. They are built primarily for data replication and typically offer minimal data transformation capabilities, provide limited support for newer database technologies, and are priced for isolated replication scenarios rather than enterprise-wide use.

Equalum’s library of high-performing, out-of-the-box Change Data Capture tools leverage all relevant APIs to capture changes from any database or non-database source, transform and enrich the data in motion, and stream changes to a data warehouse or data lake.

Design a Future-Proof Data Architecture with Confidence

Speed and Scalability

Combines unique scalability capabilities with the power of Spark and Kafka to provide extremely fast data ingestion between any number of sources and targets. Learn more

Robust Transformations

Provides transformation capabilities that go well beyond replication, including source data modification, data computations, and correlation with other data sources. Learn more


Seamless integration with newer database technology and non-database sources; zero-coding approach and no footprint on database sources. Learn more

Cost Effectiveness

An enterprise license model that enables businesses to scale their CDC investment cost-effectively. Learn more

Customer Insights


A Fortune 500 oil and natural gas exploration company struggled with previous data ingestion processes with 10 minutes latency at best, creating big operational and business risks. Developing additional data ingestion processes was very time consuming with hundreds being added every quarter.

Equalum was brought in to stream drilling rigs data, approximately 20,000 events/second with latency of 1 second from Oracle and other sources to a data analytics environment – powering real-time analytics for drill site optimization.

Trusted by Industry Leaders

Top Implementation Considerations for Successful Change Data Capture

Strategic Considerations for Successful Streaming Ingestion

It is imperative that your business has the right architecture in place to handle high throughput of data, a simplicity of replicating subsets of data and ever changing schema, as well as the capacity to capture the data and the changes exactly once, then replicate or ETL the CDC data to your data warehouse or data lakes, for analytics purposes.

In our comprehensive guide, explore the many facets to consider when deploying modern, multi-modal change data capture successfully.

Additional Resources

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