Interview: Survey from Dell Discovers Need for Big Data in Midmarket Companies

Big Data has mostly been considered the realm of big enterprise and not the midmarket segment. Dell launched a survey to study this notion and discovered that midmarket companies not only need Big Data to engender better, more competitive business practices, but many are already using data analysis. We caught up with Darin Bartik, Executive Director and GM of Database Management at Dell, to learn more about the survey and its findings.

Interview: Concurrent Leads the Way in Application Building on Hadoop

“Concurrent is the team behind Cascading, the proven application development framework that makes it possible for enterprises to leverage their existing skill sets for building data-oriented applications on Hadoop. Cascading has built-in attributes that make data application development a reliable and repeatable process. Companies that standardize on Cascading can build data applications at any scale, integrate them with existing systems, employ test-driven development practices and simplify their applications’ operational complexity.”

Interview: Why Denodo Believes Everyone Needs Data Virtualization

“The Denodo Platform delivers the capability to access any kind of data from anywhere it lives without necessarily moving it to a central location like a data warehouse. Once moved it exposes that data to various users and analytical/business applications as virtual data services in a way that is meaningful to the users, in real-time, with high performance, using caching and minimal data movement only as needed. That is data virtualization in a nutshell.”

Interview: Accenture Looks to Gather and Analyze Data at the ‘Speed of Now’

“The Democratization of Analytics doesn’t mean that every individual is or should be a data scientist, mathematician or statistician. Our solutions, products and services intend to make analytics and analytic capabilities more understandable and more available to individuals across the enterprise so they can operate more effectively and execute accurately. The Democratization of Analytics means that the enterprise can deliver more impactful outcomes, faster.”

Interview: VoltDB Powers Fast and Smart Data in Gaming World and Beyond

VoltDB is an in-memory, distributed, relational database that exceeds the performance needs of modern data-intensive applications in industries including mobile, gaming, advertising technology, financial services and energy.

Interview: Guavus Tackles Real-Time Data Analytics Across the Entire Enterprise

Guavus uses live analytics with responsive queries to garner insightful business metrics to serve up competitive advantage. “Guavas is unique in its ability to provide an end-to-end view across your business and operations in real time. Our operational intelligence platform processes over 2.5 petabytes of data per day, which equals to 250 billion records per day and 2.5 million transactions per second.”

Interview: ParStream Analyzes Billions of Records in Less than a Second

“ParStream is a columnar database with a hybrid in-memory storage and a shared nothing architecture. Based on patented algorithms for indexing and compressing data, Parstream uniquely combines three core features: Analyzing billions of records in sub seconds, continuous fast import with up to 1 million rec/s and a flexible, interactive analytics engine with a SQL interface.”

Interview: NetApp and Policy-Based Data Management for the Enterprise

“Key industries including healthcare, retail, telecommunication, media and entertainment, financial services and the government leverage NetApp solutions to manage large amounts of content, expand technology infrastructures without disrupting operations, and improve data-intensive workflows.”

Interview: A3CUBE Sets Sights on the Emerging Arena of High Performance Data

“Our architecture permits tens of thousands of SSDs to be connected together and accessed in a parallel and concurrent way using direct mapping of memory accesses from a local machine to the I/O bus and memory of a remote machine. This feature allows for data transmission between local and remote system memories without the use of operating system services. It also enables a unique linear scalability of SSDs bandwidth and IOPS and consequently allows computation and data access to scale together linearly. This totally eliminates the bottleneck in bandwidth or IOPS and provides optimal dimensions of performance, capacity, and computation with an unmatched flexibility at a fraction of the costs.”

Interview: Nexenta Seeks to Do Away with MESS

“Software defined storage is a fundamental component of software defined data centers – the next step in the evolution of virtualization and cloud computing. In its simplest form, Software Defined Storage is about leveraging software only solutions to address storage challenges, from vendor lock-in, cost, performance, security, scale and manageability. A complete SDS portfolio enables customers to both optimize existing infrastructure and fully replace legacy configurations with industry standard hardware powered by software.”