DATA INGESTION FOR HADOOP DATA LAKES
Accelerate real-time data ingestion at scale from many sources into your Data Lake
Data Lakes are the modern enterprise platform on which data architects, analysts and scientists address modern big data use cases such as fraud detection, real-time customer marketing, trend analysis, IoT and more. Whether on premises or in the Cloud, Data Lakes are a critical part of data management infrastructures.
As enterprises build data lakes, they often struggle to ingest data from many sources due to the reliance upon manual scripting and disparate collections of open-source data loading tools, such as Apache Sqoop.
Attunity Replicate provides an easy and scalable data ingest platform that supports many source database systems, delivering data efficiently and ensuring high performance to different types of data lakes.
- Attunity Won a $1.8 Million Deal Integrating SAP Data with Hadoop Data Lake at a Global Food Processing Company
- Attunity Signed a $0.8 Million Agreement with Large Global Insurance Company to Enable New Data Lake Initiative
“Using Attunity Replicate, we were able to create our strategic analytical platform, Insights Analytics, which allows us to make important operational decisions that benefit our staff and students.”
Lead for Database Admin, University of North Texas
Simple and Scalable
With Attunity Replicate, IT organizations gain:
- Simplicity – no coding. Use an intuitive and configurable GUI to quickly and easily set up data feeds with no manual coding
- Large Scale. Scale to ingest data from hundreds and thousands of databases, providing centralized monitoring and management capabilities
- Support for many source systems. One unified replication platform supports many types of sources including all major RDBMS, data warehouses, and mainframe systems
- High performance and low risk. Gain optimized and certified integration into all Hadoop distributions – Cloudera, Hortonworks, MapR, as well as Kafka and Cloud platforms
For the highest possible performance ingest incremental datasets continuously and efficiently with enterprise-class change data capture (CDC) that delivers data immediately, with near linear scalability, and virtually zero latency.