Last October, we publicly announced StreamSets Data Collector version 1.0. Over the last 12 months we have seen an awesome (a word we don't use lightly) amount of adoption of our first product – from individual developers simplifying their day-to-day work, to small startups building the next big thing, to the very largest companies building global scale enterprise architectures with StreamSets Data Collector at its core.
Kirit BasuAnnouncing StreamSets Data Collector version 2.0
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.
Arvind PrabhakarCreating a Post-Lambda World with Apache Kudu
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.
Girish PanchaIntroducing StreamSets DPM – Operational Control of Your Data in Motion
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) 220.127.116.11, 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.
Pat PattersonIngesting Drifting Data into Hive and Impala
It's been a busy summer here at StreamSets, we've been enabling some exciting use-cases for our customers, partners and the community of open-source users all over the world. We are excited to announce the newest version of the StreamSets Data Collector.
A key aspect of StreamSets Data Collector (SDC) is its ability to parse incoming data, giving you unprecedented flexibility in processing data flows. Sometimes, though, you don't need to see ‘inside' files – you just need to move them from a source to one or more destinations. Breaking news – the upcoming StreamSets Data Collector 18.104.22.168 release will include a new ‘Whole File Transfer' feature to do just that. If you're keen to try it out right now (on test data, of course!), you can download a nightly build of SDC and give it a whirl. In this blog entry I'll explain everything you need to know to be able to get started with Whole File Transfer, today!
Pat PattersonWhole File Transfer with StreamSets Data Collector