{"id":3157,"date":"2014-04-07T06:39:53","date_gmt":"2014-04-07T06:39:53","guid":{"rendered":"http:\/\/www.odbms.org\/blog\/?p=3157"},"modified":"2014-04-07T06:39:53","modified_gmt":"2014-04-07T06:39:53","slug":"robin-schumacher-vp-products-datastax","status":"publish","type":"post","link":"https:\/\/www.odbms.org\/blog\/2014\/04\/robin-schumacher-vp-products-datastax\/","title":{"rendered":"Big Data: three questions to DataStax"},"content":{"rendered":"

“High volume and data driven businesses have led to new types of data emerging from the cloud, mobile devices, social media and sensor devices. For applications processing such data, traditional relational databases such as Oracle simply run out of steam.”–Robin Schumacher<\/strong><\/p><\/blockquote>\n

The sixth interview in the \u201cBig Data: three questions to<\/em> \u201c series of interviews, is with Robin Schumacher<\/strong>, VP of Products at DataStax<\/a>.<\/p>\n

RVZ<\/p>\n

Q1. What is your current product offering?<\/strong><\/p>\n

Robin Schumacher:\u00a0<\/strong>DataStax offers the first enterprise-class NoSQL platform for data-driven,\u00a0real-time online applications. Our flagship product is DataStax Enterprise\u00a04.0<\/a>, built on Apache Cassandra<\/a>. It is a complete big data platform with\u00a0the full power of Cassandra offering a range of solutions including built\u00a0in analytics, integrated search, an in-memory options, and the most\u00a0comprehensive security feature set of any NoSQL database.
\nAn integrated analytics component allows users to store and manage line of\u00a0business application data and analyzes that same data within the platform.\u00a0The analytics capability allows for comprehensive workload management and\u00a0allows the user to run real time transactions and enterprise search\u00a0workloads in a seamlessly integrated database.
\nBuilt in search offers robust full text search, faceted search, rich\u00a0document handling and geospatial search.
\nBenefits include full workload management, continuous availability, real-time functionality and data\u00a0protection.
\nLastly, security runs through the entire platform to protect unauthorized\u00a0access to guard sensitive data. Visual backup and restore processes make\u00a0for retrieving lost data extremely easy.
\nDataStax OpsCenter<\/a>, a simplified management solution, is included with\u00a0DataStax Enterprise. This service makes it easy to manage Cassandra and\u00a0DataStax Enterprise clusters by giving administrators, architects and\u00a0developers a view of the system from a centralized dashboard. OpsCenter\u00a0installs seamlessly and gives system operators the flexibility to monitor\u00a0and manage the most complex workloads from any web browser.<\/p>\n

Q2. Who are your current customers and how do they typically use your\u00a0products?<\/strong><\/p>\n

Robin Schumacher:\u00a0<\/strong>DataStax is the first viable alternative to Oracle and powers the online\u00a0applications for 400+ customers and more than 20 of the Fortune 100. Our\u00a0customer industries range from e-commerce to education to digital\u00a0entertainment and the top use cases are the following:
\n1. Fraud detection<\/a>
\n2. The Internet of Things<\/a>
\n3. Messaging<\/a>
\n4. Personalization<\/a>
\n5. Collections\/Playlists<\/a><\/p>\n

Customers include Netflix<\/a>, eBay<\/a>, Adobe<\/a>, Amara Health Analytics<\/a> and many\u00a0others.<\/p>\n

The most common baseline use for our product is to serve as an operational\u00a0database management system for online applications that must scale to\u00a0incredible levels and must remain online at all times.<\/p>\n

Q3. What are the main new technical features you are currently working on\u00a0and why?<\/strong><\/p>\n

Robin Schumacher:\u00a0<\/strong>We recently added an in-memory option that enables companies to process\u00a0data up to 100 times faster. This option excels in use cases that require\u00a0fast write and read operations, and is particularly suited when data is\u00a0overwritten frequently, but not actually deleted. DataStax Enterprise 4.0\u00a0is the first NoSQL database to combine this in memory option with\u00a0Cassandra\u00b9s always on architecture, linear scalability and datacenter\u00a0support, delivering lightning performance that allows businesses to scale\u00a0applications with zero downtime – particularly useful in financial\u00a0services use cases or any application where performance is key.<\/p>\n

High volume and data driven businesses have led to new types of data\u00a0emerging from the cloud, mobile devices, social media and sensor devices.\u00a0For applications processing such data, traditional relational databases\u00a0such as Oracle simply run out of steam. DataStax Enterprise 4.0 offers a\u00a0powerful, modern alternative to help build online applications that scale\u00a0as the business grows. This in-memory capability equals faster\u00a0performance, easy development, flexible performance management and\u00a0seamless search:
\nObjects created in-memory optimize performance and deliver increased speed\u00a0which enables businesses to deliver data to customers faster than ever\u00a0before.
\nIn-memory objects act as Cassandra tables so they are transparent to\u00a0applications and developers have no learning curve to\u00a0manage.Administrators can decide where to assign data, making performance\u00a0optimization easier than ever.<\/p>\n

Enhanced internal cluster communications deliver faster search operations\u00a0help developers build applications more efficiently.<\/p>\n

Related Posts<\/strong><\/p>\n

– Big Data: Three questions to Aerospike. ODBMS Industry Watch, March 2, 2014<\/a><\/p>\n

–\u00a0Big Data: Three questions to McObject. ODBMS Industry Watch, February 14, 2014<\/a><\/p>\n

–\u00a0Big Data: Three questions to VoltDB. ODBMS Industry Watch, February 6, 2014.<\/a><\/p>\n

–\u00a0Big Data: Three questions to Pivotal. ODBMS Industry Watch, January 20, 2014.<\/a><\/p>\n

–Big Data: Three questions to InterSystems. ODBMS Industry Watch, January 13, 2014.<\/a><\/p>\n

–\u00a0Operational Database Management Systems. Interview with Nick Heudecker, ODBMS Industry Watch, December 16, 2013.<\/a><\/p>\n

Resources<\/strong><\/p>\n

– ODBMS.org: free download of technical resources on DataStax<\/a><\/p>\n

– ODBMS.org: free download of technical resources on Apache Cassandra<\/a><\/p>\n

– 2013 Gartner Magic Quadrant for Operational Database Management Systems by Donald Feinberg, Merv Adrian, Nick Heudecker, October 21, 2013<\/a><\/p>\n

Follow ODBMS.org on Twitter<\/strong>:\u00a0@odbmsorg<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

“High volume and data driven businesses have led to new types of data emerging from the cloud, mobile devices, social media and sensor devices. For applications processing such data, traditional relational databases such as Oracle simply run out of steam.”–Robin Schumacher The sixth interview in the \u201cBig Data: three questions to \u201c series of interviews, […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/3157"}],"collection":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/comments?post=3157"}],"version-history":[{"count":19,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/3157\/revisions"}],"predecessor-version":[{"id":3185,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/posts\/3157\/revisions\/3185"}],"wp:attachment":[{"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/media?parent=3157"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/categories?post=3157"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.odbms.org\/blog\/wp-json\/wp\/v2\/tags?post=3157"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}