DataTorrent RTS provides a single, unified batch and stream processing platform that enables organizations to reduce time to market, development costs and operational expenditures for big data analytics applications. With DataTorrent RTS, organizations can streamline their batch and streaming data processing with a data pipeline approach. Analyzing data while it is motion and automating actions to be taken drives faster business value, while still preserving existing business processes for ad-hoc processing.

about the company


Phu came out of retirement to join Kiva in 2009 and served as Kiva's VP of Product Development. Phu left Viet Nam along with his family in April 1975, when he was 10 years old. He considers himself extremely fortunate in his life in America and is thrilled to be able to help others get a similar opportunity to improve their lives. Prior to Kiva, Phu spent over 11 years at Yahoo heading up Engineering for Yahoo's consumer web sites, advertising systems, and platform. His greatest gift in life is his wife Tamar and their three children: Jason, Grace, and Allison. Phu hurts himself frequently playing basketball, tennis, and poker. He studied at the University of Maryland, College Park and the University of California, Berkeley

Thomas is a principal architect at DataTorrent. Thomas has extensive experience architecting and developing real-time streaming applications based on Hadoop. Before joining Datatorrent Thomas was part of the Hadoop engineering team at Yahoo.

CTO and Co-Founder

DataTorrent in the press

May 18, 2016

Cazena’s Big Data-as-a-Service offering lands on Azure

“Our launch on Microsoft Azure extends Cazena’s vision of big data on demand for enterprises.”Cazena’s premise is simple – businesses can use it to offload workloads to the cloud, analyze Big Data sources from outside their network (including data from social networks etc. “Cazena will help accelerate customers’ ability to migrate Big Data workloads to Microsoft Azure,” said Steve Guggenheimer, corporate vice president and chief evangelist, Developer Experience at Microsoft. Big Data-as-a-Service startup (BDaaS) Cazena Inc., which burst onto the scene just last year, has said it’s flagship offering can now be used with Microsoft Azure, giving customers faster access to on-demand data processing and analytics. Cazena is betting that support for Azure will be extremely attractive to the thousands of enterprises that currently use Microsoft’s cloud. Using Cazena on Microsoft Azure is one way of doing that, because it only requires a very low investment on extra resources in order to be able to use it.

April 26, 2016

Spark rival Apache Apex hits top-level status

Apache Apex was yesterday moved up to become the Apache Software Foundation (ASF)’s latest top-level project. Thomas Weise, Apache Apex PMC member, said, “It is very exciting to see Apex after nearly four years since inception becoming an ASF top-level project. Apache Apex is an open-source stream and batch processing platform that’s compatible with HDFS and YARN, runs in-memory, and offers enhanced event processing and fault tolerance capabilities. “Apache Apex meets the demands of today’s Big Data applications with real-time reporting, monitoring, and learning with millisecond data point precision,” the ASF said in a statement. Apex is highly performant, linearly scalable, fault tolerant, stateful, secure, distributed, easily operable with low latency, no data loss, and exactly-once semantics.”Some might be forgiven for thinking that Apache Apex sounds a bit too similar to more well-known stream processing engines like Apache Spark, and the more specialized Apache Storm and Apache Samza, and it is.

April 16, 2016

15 "True" Streaming Analytics Platforms For Real-Time Everything