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The DataOps Blog

Where Change Is Welcome

Ingesting Streaming Data from JMS into HDFS and Solr using StreamSets

Engineering, Use Cases, StreamSets News, StreamSets Partners

A step-by-step walkthrough of how Mac Noland implemented StreamSets to move away from hand-coded ETL and scale out an increasingly complex ingestion pipeline. Mac is a Solution Architect for phData, a Twin Cities services firm focused on Hadoop. He has spent 17 years as a software engineer and architect for projects in the legal, accounting, risk and medical device industries.

By November 10, 2015

Using Open Source StreamSets to Tackle Data Drift (video)

Use Cases, Videos, Industry

Watch StreamSets Field Engineer Jonathan "Natty" Natkins demonstrate how you can use the open source StreamSets Data Collector to flexibly handle painful "data drift" - the inevitable evolution of infrastructure, semantics and schema that leads to corrupted data and broken pipelines.   Download Open Source StreamSets Data Collector at www.streamsets.com/opensource.

By October 27, 2015

Introducing the StreamSets Data Collector (video)

Engineering, Videos, StreamSets News

Wondering how the StreamSets Data Collector works? Have a look at this quick 4 minute introduction to the software.

By October 8, 2015

What is StreamSets? (video)

Videos, StreamSets News

StreamSets is an open source, enterprise-grade, continuous big data ingest infrastructure that accelerates time to analysis by bringing unprecedented transparency and processing to data in motion. Watch co-founders Girish Pancha (CEO) and Arvind Prabhakar (CTO) talk about the problems they are trying to solve with StreamSets.

By October 5, 2015

State of the Art Data Ingestion

StreamSets News

Forward-looking, data-driven enterprises increasingly leverage Big Data platforms, such as Hadoop, Elasticsearch and Amazon Web Services, to derive insights from non-­transactional, machine­-generated data. Many tools have emerged to power next ­generation data pipelines and provide specialized analytic capabilities. To get value from these technologies, data must reside in intermediate data stores in a consumable form. However, existing data integration tools do not…

By September 29, 2015
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