DataTorrent

DataTorrent empowers customers to make their decisions matter. Whether your data comes from machines, people or automated systems, we enable you to build and deploy production applications easily and rapidly while extracting relevant insights to make real-time decisions. With the DataTorrent RTS Platform for streaming data and Factory, you'll simplify data integration, enrichment, and analytics—spurring your business to act quickly and with immediate impact.



about the company

Founders

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

March 1, 2017

Realtime data ingestor DataTorrent gets led Churchward

Former EMCer Guy Churchward has taken the reins at DataTorrent as CEO and president. In December 2016 Churchward resigned as Core Technologies Division president at EMC after its purchase by Dell. He stayed on at EMC, before joining DataTorrent to assist with the transition to its new organisational structure. DataTorrent is a Big Data streaming analytics company founded in 2012 by ex-Yahoo! Every enterprise is focused on creating knowledge from data as it's created – DataTorrent is uniquely poised to deliver that knowledge to its customers."

Dec. 12, 2016

DataTorrent Names Guy Churchward As New CEO

DataTorrent announced today its Board of Directors unanimously appointed Guy Churchward as President and Chief Executive Officer effective February 2017. “We are ecstatic to have Guy join DataTorrent as its Chief Executive Officer,” said David Hornik of August Capital. Over the past eighteen months we’ve seen high profile multinational enterprises deploy DataTorrent’s solution in 24x7 mission critical applications with tremendous success. Prior to joining EMC, Churchward was President and CEO of LogLogic, an enterprise log and security intelligence platform company. Guy is a welcome addition to DataTorrent who will help us refine our market leading solution, scale our business and set the strategy for our next chapter.”“I’m sincerely honored to be part of the DataTorrent team,” said Guy Churchward.

Sept. 30, 2016

Redefining Hadoop for better data insights

This program will make it simpler for enterprises to choose and adopt Big Data technologies and ensures these applications are interoperable across a wider range of commercial Hadoop platforms. Defining Hadoop differentlyVellante asked if IBM is building into a new Hadoop distribution with ODPi as the framework. “We’ve had [IBM’s] Big SQL for many years … but the market in the distribution market is fragmented. ODPi is trying to do the same thing for the Hadoop ecosystem,” said Schiefer. “Today, I think that Hadoop should be redefined as an ecosystem of collaborative tools … very much like Unix became.

Sept. 28, 2016

More Hadoop vendors back controversial Open Data Platform initiative

The controversial Open Data Platform initiative (ODPi) has shied away from the spotlight in recent months, but yesterday announced that a number of prominent enterprise vendors have jumped onto its bandwagon. and Xavient Information Systems have all signed on to its interoperability program, and will henceforth commit to making their applications and software platforms interoperable with each other. But the other two major Hadoop vendors, Cloudera Inc. and MapR Technologies Inc., refused to join the consortium, denouncing it as a self-serving initiative that would only benefit the vendors involved. To date, Altiscale, ArenaData, Hortonworks, IBM and Infosys’ Hadoop platforms have all been certified as compliant. “ODPi is providing a common platform to develop big data apps, enabling interoperability across different distributions and application offerings,” Ritika Gunnar, vice president of Offering Management, Data and Analytics at IBM, said in a statement.

Sept. 27, 2016

IBM, WanDisco, DataTorrent and pals sign Hadoop interoperability pact

The initiative created to standardise Apache Hadoop applications has netted a handful of large enterprise vendors that have committed to its interoperability programme. ODPi published its first runtime specification to establish the technical necessities of that interoperability back in May. Additionally, ODPi announced today that version 2.0 of its runtime specification will add Apache Hive and Hadoop Compatible File System support. In that spirit, IBM is ensuring many of our Apache Hadoop related offerings are interoperable including IBM Big SQL, IBM SPSS Analytic Server, IBM Big Replicate, and others. "By supporting interoperable applications, the value to clients of ODPi Compliant distributions is beingenhanced," added Gunnar.

Aug. 9, 2016

GigaSpaces opens up its in-memory data grid

More and more data management vendors are open-sourcing their software. The company this morning announced plans to make the core component of its XAP in-memory computing framework available under a free license. Though the system is not as well-known as SAP SA’s HANA in-memory store or Apache Spark, it’s achieved tremendous success since hitting the market 15 years ago. GigaSpaces hopes that open-sourcing the core capabilities of XAP will broaden its appeal even further. GigaSpaces hopes to address the demand by rolling out two new commercial editions of its offering alongside the open-source version.

May 18, 2016

Cazena’s big data-as-a-service offering lands on Azure

Big data-as-a-service startup (BDaaS) Cazena Inc., which burst onto the scene just last year, has said its 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 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. 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.

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. 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. 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.

April 16, 2016

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

Streaming Analytics Captures Real-Time IntelligenceMost enterprises aren’t fully exploiting real-time streaming data that flows from IoT devices and mobile, web, and enterprise apps. Forrester Wave™: Big Data Streaming Analytics, Q1 2016To help enterprises understand what commercial and open source options are available, Rowan Curran and I evaluated 15 streaming analytics vendors using Forrester’s Wave methodology. Its current modus operandi is to engineer the best open source streaming analytics (that can also do batch processing). Its current modus operandi is to engineer the best open source streaming analytics (that can also do batch processing). It can ingest streaming data from many sources, including streaming change data capture (CDC) from transactions in databases.

Dec. 30, 2015

Big Data Predictions for 2016

In terms of manageability, Big Data tooling needs to achieve not just parity with data warehousing and BI tools, but needs to surpass that level. Venugopal, in fact, feels that we are within two years of streaming data becoming looked upon as just another data source. But even if not, he's absolutely right that this functionality is needed in the Big Data world. And that's a great sign for everyone involved in Big Data. Essentially, value and maturity are proxies for the enterprise-readiness of Big Data platforms.

Dec. 30, 2015

Big Data Predictions for 2016

In terms of manageability, Big Data tooling needs to achieve not just parity with data warehousing and BI tools, but needs to surpass that level. Venugopal, in fact, feels that we are within two years of streaming data becoming looked upon as just another data source. But even if not, he's absolutely right that this functionality is needed in the Big Data world. And that's a great sign for everyone involved in Big Data. Essentially, value and maturity are proxies for the enterprise-readiness of Big Data platforms.

Dec. 28, 2015

10 top big data and analytics stories of 2015

Many big companies today do a great job of collecting big data. Big data, business analytics and marketing experts discuss how organizations can best put to use all that consumer data they've been collecting. Wireless biosensors and big data analytics can help hospitals identify patients showing signs of sepsis, the leading cause of death in noncoronary intensive care units in the U.S. Here's how seven companies have taken advantage of new technology to drive big data. As in 2014, data and analytics were a hot topic at CIO.com in 2015.

Dec. 14, 2015

Solace and DataTorrent Partner to Enable Real-Time Ingestion and Analysis of Streaming Big Data

About DataTorrentDataTorrent is the leader in real-time big data analytics. DataTorrent RTS is the industry's only solution to have a high performing, fault tolerant unified architecture for both data in motion and data at rest. "Competitive pressures in the evolving big data market are driving demand for real-time streaming and data ingestion tools that can seamlessly integrate valuable insights into business operations," said Charu Madan, director of business development, DataTorrent. Solace and DataTorrent both offer elastic capacity to keep up with rising data volumes, and DataTorrent is one of the few applications that can scale to capture as much data as Solace can deliver. DataTorrent RTS is proven in production environments to reduce time to market, development costs and operational expenditures for Fortune 100 and leading Internet companies.

Dec. 8, 2015

MapR Announces MapR Streams, Creating the Industry's First and Only Converged Data Platform

The MapR Converged Data Platform integrates file, database, stream processing, and analytics to accelerate data-driven applications and address emerging IoT (Internet of Things) needs. The integration of MapR Streams into a converged platform enables organizations in any industry to continuously collect, analyze and act on streaming data. We are seeing the converged MapR platform with MapR Streams delivering more real-time data services to our users, while enhancing those important criteria.”Unlike other approaches that create data silos across multiple systems and lack the required enterprise-grade features and global replication, only MapR natively integrates data-in-motion and data-at-rest in one converged data platform. “We continue to be impressed with the innovative new features MapR has been integrating into its data platform,” said Brad Anderson, vice president, big data informatics, Liaison Technologies. Enterprise-grade, high-throughput streaming converges data-in-motion with data-at-restSAN JOSE,Calif.–(BUSINESS WIRE)–December 8, 2015–MapR Technologies, Inc. today announced the industry’s first and only converged data platform and introduced MapR Streams, a reliable, global event streaming system that connects data producers and data consumers across shared topics of information.

Dec. 8, 2015

MapR Announces MapR Streams, Creating the Industry’s First and Only Converged Data Platform

The MapR Converged Data Platform integrates file, database, stream processing, and analytics to accelerate data-driven applications and address emerging IoT (Internet of Things) needs. The integration of MapR Streams into a converged platform enables organizations in any industry to continuously collect, analyze and act on streaming data. We are seeing the converged MapR platform with MapR Streams delivering more real-time data services to our users, while enhancing those important criteria.”Unlike other approaches that create data silos across multiple systems and lack the required enterprise-grade features and global replication, only MapR natively integrates data-in-motion and data-at-rest in one converged data platform. SAN JOSE,Calif.--(BUSINESS WIRE)--MapR Technologies, Inc. today announced the industry’s first and only converged data platform and introduced MapR Streams, a reliable, global event streaming system that connects data producers and data consumers across shared topics of information. “We continue to be impressed with the innovative new features MapR has been integrating into its data platform,” said Brad Anderson, vice president, big data informatics, Liaison Technologies.

Dec. 3, 2015

Cisco Extends SDN Leadership With New ACI Capabilities

SUPPORTING RESOURCESLearn more about: Application Centric Infrastructure (ACI)Read InfoWorld's in-depth product review of ACI: "Cisco ACI shakes up SDN"Read IDC Report: Symantec Delivering on Its Strategic Vision with Next-Generation Secure Datacenter Powered by Cisco ACIView video: "Applications Leaders Embrace ACI"View ACI animated videos: "One Day at a Large Financial Institution", "Fixing an Application with Cisco ACI", "Upgrading an Application with Cisco ACI", "Cisco ACI and IT Security Automation Saves the Day"Learn How Cisco ACI delivers business outcomesLearn more on Cisco Data Center ServicesAbout CiscoCisco ( NASDAQ : CSCO) is the worldwide leader in IT that helps companies seize the opportunities of tomorrow by proving that amazing things can happen when you connect the previously unconnected. Cisco delivers support for both physical and virtual endpoints, and now extends support for Docker container endpoints through integration with the Cisco Application Policy Infrastructure Controller (APIC) and Project Contiv. Cisco ACI now also supports service insertion and chaining for any service device, without the need for a device package for policy coordination with the Cisco APIC. Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. Cisco also added integration of Docker containers through contributions to open source, offering customers a consistent policy model and greater deployment flexibility using the Cisco Application Policy Infrastructure Controller (APIC).

Dec. 1, 2015

Impala, Kudu, and the Apache Incubator's four-month Big Data binge

This leaves us with a great number of Apache Incubator projects that overlap, with each other and with certain Apache Software Foundation (ASF) top-level projects. The redundancy and competition are both drivers of innovation and fragmenting forces in the Big Data market. Then the ecosystem's only problem will be choosing between Hive, Impala, Spark SQL and Drill, all of which will be Apache projects. Well, the company open sourced it, as an Apache project, with acceptance into the Apache Incubator coming this past September. Just since August of this year, the Apache Incubator has welcomed, or been asked to consider, an array of new projects from the Big Data world.

Oct. 31, 2015

How Apache Kafka is greasing the wheels for big data

Originally developed at LinkedIn, Kafka is an open-source system for managing real-time streams of data from websites, applications and sensors. Since being conceived at LinkedIn, Kafka has gained high-profile support from companies such as Netflix, Uber, Cisco and Goldman Sachs. In general, there's a marked trend toward real-time data, Hopkins said. Up until 2013 or so, "big data was all about massive quantities of data stuffed into Hadoop," he said. That's where Apache Kafka comes in.

Oct. 30, 2015

How Apache Kafka is greasing the wheels for big data

Originally developed at LinkedIn, Kafka is an open-source system for managing real-time streams of data from websites, applications and sensors. Since being conceived at LinkedIn, Kafka has gained high-profile support from companies such as Netflix, Uber, Cisco and Goldman Sachs. "Besides ActiveMQ and RabbitMQ, another product offering similar functionality is Apache Flume, he noted; Storm and Spark Streaming are similar in many ways as well. In general, there's a marked trend toward real-time data, Hopkins said. Up until 2013 or so, "big data was all about massive quantities of data stuffed into Hadoop," he said.