Centralizing data from across the enterprise into public cloud data lakes or Apache Hadoop typically requires extensive custom coding and ongoing maintenance. Engineering teams must build connectors to enterprise applications (like ERPs or CRMs), extract data from operational databases in a low-footprint manner, load in data from file formats like XML, .csv, or JSON, and manage unwieldy new data sources like equipment sensors and IoT control systems. Custom scripting is expensive and time-consuming, while batch ETL jobs fail under heavy loads and are not equipped to handle schema changes over time.
Equalum makes it easy to replicate data from throughout the enterprise to data lakes like AWS, Microsoft Azure, Google Cloud Platform, and Apache Hadoop. Equalum’s technology connects seamlessly to any data source, leverages best-in-class change data capture (CDC) to extract data changes with minimal impact to the underlying system, and delivers data to data lakes in either streaming or batch fashion. Equalum uniquely combines its native technology with the scalability of open source big data frameworks like Spark and Kafka to dramatically improve the performance of data pipelines – enabling organizations to increase data volumes while reducing processing time.
Accelerate consolidation and realize the full potential of their data lakes
Equalum’s engine, powered by Spark and Kafka, delivers data in real-time or batch from anywhere in the organization – ensuring that data lakes can capture all enterprise data to power real-time analytics.
Extract data without impacting source applications
The most robust CDC on the market captures database changes in real-time with minimal overhead.
Build data pipelines in minutes
Equalum’s zero-coding interface makes it easy to configure, transform, and transfer data from any source.
A Fortune 500 oil and petroleum exploration company uses Equalum to stream up to a million events per second – with latency of less than a second – to a centralized data lake, while formatting and enriching data along the way.
We look forward to being part of the upcoming webinar presented by TDWI. At the end of the webinar you will have a clear...
We look forward to being part of this upcoming webinar presented by PostgresConf. At the end of the webinar you will learn how to...