Announcing StreamSets Data Collector version 2.0
StreamSets Data Integration Blog
Where change is welcome.
MySQL CDC with MapR Streams, Apache Drill, and StreamSets
Today’s post is from Raphaël Velfre, a senior data engineer at MapR. Raphaël has spent some time working with StreamSets Data Collector (SDC) and MapR’s Converged Data Platform. In this blog entry, Raphaël explains how to use SDC for MySQL CDC to extract data from MySQL and write it to MapR Streams, and then move data from MapR Streams to MapR-FS via SDC, where it can be queried with Apache Drill.
Creating a Post-Lambda World with Apache Kudu
Apache Kudu and Open Source StreamSets Data Collector Simplify Batch and Real-Time Processing
As originally posted on the Cloudera VISION Blog.
At StreamSets, we come across dataflow challenges for a variety of applications. Our product, StreamSets Data Collector is an open-source any-to-any dataflow system that ensures that all your data is safely delivered in the various systems of your choice. At its core is the ability to handle data drift that allows these dataflow pipelines to evolve with your changing data landscape without incurring redesign costs.
This position at the front of the data pipeline has given us visibility into various use cases, and we have found that many applications rely on patched-together architectures to achieve their objective.
Building a Data Science Pipeline at IBM Ireland with StreamSets
After Guglielmo Iozzia, a big data infrastructure engineer on the Ethical Hacking Team at IBM Ireland, recently spoke about building a data science pipeline using StreamSets Data Collector Engine at Hadoop User Group Ireland, I invited him to contribute a blog post outlining how he discovered StreamSets Data Collector (SDC) Engine and the kinds of problems he and his team are solving with it. Read on to discover how SDC is saving time and making Guglielmo and his team’s lives a whole lot easier.
Introducing StreamSets DPM – Operational Control of Your Data in Motion
Friends of StreamSets,
Today I am delighted to announce our new product, StreamSets Dataflow Performance Manager, or DPM, the industry’s first solution for managing operations of a company’s end-to-end dataflows within a single pane of glass. The result of a year’s worth of innovative engineering and collaboration with key customers, DPM will be generally available on or before September 27, in time for Strata. We invite you to come by our booth (#451) for a live demonstration.
DPM is a natural follow-on to our first product, StreamSets Data Collector, which is open source software for building and deploying any-to-any dataflow pipelines. That product has enjoyed a great deal of success in its first year in market, with an accelerating number of weekly downloads, which now total in the tens of thousands across hundreds of enterprises, and numerous production use cases in Fortune 500 companies across a variety of industries.
Ingesting Drifting Data into Hive and Impala
Importing data into Apache Hive is one of the most common use cases in big data ingest, but gets tricky when data sources ‘drift’, changing the schema or semantics of incoming data. Introduced in StreamSets Data Collector (SDC) 1.5.0.0, the Hive Drift Solution monitors the structure of incoming data, detecting schema drift and updating the Hive Metastore accordingly, allowing data to keep flowing. In this blog entry, I’ll give you an overview of the Hive Drift Solution and explain how you can try it out for yourself, today.
Announcing Data Collector ver 1.6.0.0
This version has a host of new features and over 100 bug fixes.