Welcome!

Containers Expo Blog Authors: Liz McMillan, Pat Romanski, Yeshim Deniz, Elizabeth White, Zakia Bouachraoui

News Feed Item

DataStax Enterprise 2.0 Adds Enterprise Search Capabilities to Smart Big Data Platform

Combination of Apache Cassandra™, Apache Hadoop™, and Apache Solr™ Creates Big Data Platform for Real-Time, Analytics, and Search Data Management

SAN MATEO, Calif., March 21, 2012 /PRNewswire/ -- GigaOm Structure (#dataconf) -- DataStax, the commercial leader in Apache Cassandra, today announced DataStax Enterprise 2.0 (DSE 2.0), the industry's first complete big data solution designed to manage real-time, analytic, and now enterprise search data, all in the same database cluster. The platform delivers a comprehensive, integrated data management solution that manages real-time data with Cassandra, provides batch analytic capabilities with Apache Hadoop, and enables enterprise search on that same data with Apache Solr.

(Logo:  http://photos.prnewswire.com/prnh/20120321/NY74004LOGO )

"Enterprise search is a high-demand capability, and open-source Apache Solr is the most popular open source search technology available," said Billy Bosworth, CEO, DataStax. "Solr downloads outnumber even Hadoop downloads today[1]. With DSE 2.0, we're allowing our customers to move faster in response to never ending user demands, by letting them focus on building big data applications instead of battling their infrastructure." 

By combining the search capabilities of Solr with the real-time and analytic database capabilities of Cassandra and Hadoop, DataStax Enterprise 2.0 provides Google-like capability for your database, with the added benefit of not needing to implement time-consuming and error-prone data movement routines.  Further, because DataStax Enterprise 2.0 is built on Cassandra, the platform delivers a scalable Solr for enterprise search with no single points of failure.  It also provides real-time search operations, full data durability, scalable and performant write operations across multiple datacenters, automatic data sharding, and easy index rebuild operations, none of which are found in native Solr. Lastly, in addition to the native Solr API's, developers can access Solr/search information using the SQL-like Cassandra Query Language (CQL), which makes it easy to query data stored in Solr.

With DataStax Enterprise 2.0, you can run real-time, analytic, and search operations in the same database cluster without any of the workloads affecting the other from a performance or resource contention standpoint.  The platform does not require time-consuming or expensive ETL software to move data between systems, because everything is automatically and transparently replicated in the cluster, even if that cluster spans multiple datacenters or is implemented in the cloud. 

"As a leading online video game subscription service, we wanted to enrich the customer experience by enabling our gamers to interact with each other and create a community," said Christian Carollo of GameFly. "With DataStax Enterprise integrating all aspects of data access into one robust data solution, it has allowed us to easily expand our platform and its feature set, thereby enhancing our products and users' experience."

SourceNinja, a leader in helping organizations manage open source, uses DSE 2.0 to correlate multiple distributions of a single open source project to a single project.  "For example, Linux is a single project - but there are multiple distributions and versions of Linux - Red Hat, Debian, Amazon and more," said Matt Stump, Co-founder, SourceNinja. "With all the different versions available, a search solution like what's in DataStax Enterprise 2.0 is really the only option that makes sense to keep all projects straight."

"With DataStax Enterprise, DataStax introduced the ability to use the same database cluster to support operational and analytic workloads. With version 2.0 the company has taken that one step further with the integration of enterprise search and elastic workload re-provisioning," said Matt Aslett, research manager, data management and analytics, 451 Research. "The new capabilities expand the way companies are able to use and analyze their data, avoiding the need to host redundant systems that have to be kept in-synch."

Other new functionality in DataStax Enterprise 2.0

DataStax Enterprise 2.0 now also includes RDBMS integration for all of the market-leading databases, making it simple to export data from your previous-generation database. And built-in utilities make it easy for developers to store, index and search application or web logs.

Finally, DataStax Enterprise 2.0 provides the ability to easily adjust the performance and capacity for various workloads. For example, the solution enables the creation of the perfect environment for retailers running major online ecommerce applications. Customers can assign a number of nodes to handle real-time operations during the day for transactional or shopping cart management. At night, they can reassign those same nodes to be Hadoop nodes, and run batch analytics on the data that was collected.

Key Benefits of DataStax Enterprise 2.0 include:

  • Fully integrated smart big data platform
  • Production certified Cassandra
  • The only integrated, scalable, fault-tolerant enterprise search with Solr 
  • Continuously available analytics with Hadoop
  • Built-in workload isolation
  • No costly and error-prone ETL operations
  • Easy migration of RDBMS and log data
  • Simple to install and grow
  • OpsCenter Enterprise, a visual management solution for big data platforms
  • 80-90% less cost than major RDBMS vendors

DataStax Enterprise 2.0 is currently available for download. For more information, please call 650-389-6000 or email [email protected].

About DataStax
DataStax offers products and services based on the popular open-source database, Apache Cassandra™, which solve today's most challenging big data problems.  DataStax Enterprise combines the performance of Cassandra with analytics powered by Apache Hadoop and enterprise search with Apache Solr, creating a smartly integrated, big data platform. With DataStax Enterprise, real-time, analytic, and search workloads never conflict, giving you maximum performance with the added benefit of only managing a single database.

The company has over 140 customers, including leaders such as Netflix, Disney, Cisco, Rackspace and Constant Contact, and spans verticals including web, financial services, telecommunications, logistics and government. DataStax is backed by industry leading investors, including Lightspeed Venture Partners and Crosslink Capital, and is based in San Mateo, CA.

[1] http://people.apache.org/~vgritsenko/stats/projects/hadoop.html  

http://people.apache.org/~vgritsenko/stats/projects/lucene.html

 

SOURCE DataStax

More Stories By PR Newswire

Copyright © 2007 PR Newswire. All rights reserved. Republication or redistribution of PRNewswire content is expressly prohibited without the prior written consent of PRNewswire. PRNewswire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

IoT & Smart Cities Stories
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-c...
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by ...
The explosion of new web/cloud/IoT-based applications and the data they generate are transforming our world right before our eyes. In this rush to adopt these new technologies, organizations are often ignoring fundamental questions concerning who owns the data and failing to ask for permission to conduct invasive surveillance of their customers. Organizations that are not transparent about how their systems gather data telemetry without offering shared data ownership risk product rejection, regu...
René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
Poor data quality and analytics drive down business value. In fact, Gartner estimated that the average financial impact of poor data quality on organizations is $9.7 million per year. But bad data is much more than a cost center. By eroding trust in information, analytics and the business decisions based on these, it is a serious impediment to digital transformation.
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Digital Transformation and Disruption, Amazon Style - What You Can Learn. Chris Kocher is a co-founder of Grey Heron, a management and strategic marketing consulting firm. He has 25+ years in both strategic and hands-on operating experience helping executives and investors build revenues and shareholder value. He has consulted with over 130 companies on innovating with new business models, product strategies and monetization. Chris has held management positions at HP and Symantec in addition to ...
Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.
As IoT continues to increase momentum, so does the associated risk. Secure Device Lifecycle Management (DLM) is ranked as one of the most important technology areas of IoT. Driving this trend is the realization that secure support for IoT devices provides companies the ability to deliver high-quality, reliable, secure offerings faster, create new revenue streams, and reduce support costs, all while building a competitive advantage in their markets. In this session, we will use customer use cases...