Last week saw evidence for the big data industry steamroller effect as the Strata Conference 2014 in Santa Clara came and went. With thousands of attendees, an abundance of informative presentations, and a very healthy exhibitor ecosystem, the show defined the current state-of-the-art for all that is big data. If you missed the big event, O’Reilly Media has graciously made available the slides and videos for some of the presentations.
H2O, the open source in-memory machine learning and predictive analytics company for big data, announced a partnership with Cloudera, a leader in enterprise data management powered by Apache™ Hadoop.
Guavus, the provider of big data analytics solutions, today announced a platform update that extends the power of real-time analytics applications throughout a virtual infrastructure. The Guavus Reflex™ Platform is an operational intelligence technology that can be deployed in virtualized service infrastructures to provide Communication Service Providers (CSPs) with critical customer information in real-time.
In this slidecast, Dev Patel and Poulomi Damany from BitYota describe the company’s Data Warehouse Service. “We are a Data Warehouse Service (DWS) available on major cloud providers like Rackspace and Amazon. We are designed from the ground up for high performance analytics on JSON data from fast-changing applications including web & mobile analytics and NoSQL stores like MongoDB. We don’t impact your operational store or app and best of all, as a fully managed service, we take the headache out of having to set up and manage another data platform.”
MemSQL, a leading supplier of distributed in-memory database technology, recently announced MemSQL v3.0, which combines a high-performance in-memory row store with a new highly compressed column store. This integration provides a tiered storage architecture that leverages memory for real-time transactions and analytics, and a flash-optimized column store for deep analysis.
“The term and current marketing around “Big Data” may be over-spun, but it’s clear that the ability to store and process lots of data will unlock many interesting use cases that were simply not even considered to be requirements in the past. There are certainly going to be an increasing number of companies and sites that focus on analyzing the data they are generating and collecting with an eye to generating valuable insights – answers to questions like “in what geographical location do my products sell the most?” and “what demographic buys my highest margin products?”