Start Reducing TCO and Accelerating Time-to-Value of Big Data
Previously, we announced the Teradata Appliance for Hadoop 5 with Cloudera. Today, we are happy announce the general availability of the Appliance, and very happy to host this guest blog from Chris Twogood, Vice President of Product and Services Marketing at Teradata Corporation.
Hadoop has come a long way since its birth nearly a decade ago. This change of the product is reflective of the changing demands in the big data industry, a phenomenon that we are observing in New York City this week at Strata + Hadoop World Conference. As the trusted advisor of data management technology over the last few decades, we noticed the conversation has shifted from the details of the different Hadoop projects to the business outcomes and competitive advantages gained by having a big data platform. We are also often asked by many of the big data “fast followers” as to how best to quickly and economically put together an enterprise grade big data platform that accelerates time to value and minimizes risk.
Recognizing the need to stand up a Hadoop cluster quickly and cost-effectively, Teradata and Cloudera have worked closely in the last couple years and today are proud to announce the ability to now take orders for Teradata Appliance for Hadoop 5 with Cloudera. By minimizing the number of moving parts required for deployment and operations, the appliance allows companies to achieve faster time to value by just plugging the appliance into existing infrastructure, thereby leveraging your current investments in technology and resources to complete the picture of Teradata’s Unified Data Architecture (UDA).
Having an appliance allows organizations to:
- Realize faster time to value from big data – The Teradata Appliance for Hadoop is delivered ready to-run so that organizations can be up and running in days, not months.
- Benefit from best in class high availability – The Teradata Appliance for Hadoop runs IP traffic over the BYNET protocol for load balancing and automatic failover built-in, which avoids the typical single point of failure.
- Lower Total Cost of Ownership (TCO) – Typical Do-It-Yourself Hadoop deployments, despite low hardware acquisition costs, experience higher overall total costs because of costs involved in setting up, testing, and running production grade Hadoop clusters. When the set up costs of multiple software installs, network configuration, disk configuration, tuning, and network integration with existing data systems like the IDW are factored in, the ready-to-run appliance becomes more cost-effective than DIY.
- Streamline support – The appliance and entire ecosystem is fully supported by Teradata’s world class support organization, providing 24×7, multi-language service and support.
- Pre-built UDA integration – The value of big data is beyond just the ability to capture, store, process, and explore unstructured data. The ability to integrate to existing data sources and leverage the unique capabilities of the enterprise data warehouse and a data discovery platform is critical to the success of any big data initiative. Joint engineering between Cloudera and Teradata has resulted in robust orchestration software that allows for pre-built integration with Cloudera Enterprise, Teradata Database, Teradata Aster Discovery Platform, and other components of the ecosystem. This integration allows users to seamlessly ingest and access data across the ecosystem in a way that minimizes complexity and costs.
Teradata Appliance for Hadoop with Cloudera
Cloudera Enterprise offers organizations the ability to run a growing and varied set of workloads from batch processing of extreme data sets to real-time analytics. Matching the advancement of Cloudera Enterprise, the new Teradata Appliance for Hadoop with Cloudera is available in multiple system configurations, depending on your performance, capacity, and workload requirements. All configurations of the appliance leverage the Intel® Core™ Processor (Haswell) technology that sets the standard for processing versatility and performance.
- Performance configuration is optimized for computation; with a faster CPU, higher memory for I/O intensive workloads, and is ideally suited for streaming applications running Spark, Storm, and SQL-on-Hadoop tools such as Impala. Performance data nodes are configured with dual 12-core processors, 24 – 1.2TB drives, and from 256 to 512GB of memory.
- Capacity configuration is optimized for long term storage and online archival to achieve the lowest cost per TB. It utilizes high capacity disks, fewer cores, and less memory, and is ideally suited for storing colder data and processing long-running ETL and analytics jobs. Capacity data nodes are configured with dual 8-core processors, 12 – 4TB drives, and from 128 to 256GB of memory.
- Balanced configuration strikes a compromise between Performance and Capacity. It provides cost savings with high capacity drives and is well-suited for ETL and analytics that are more CPU intensive with less demanding I/O requirements. Balanced nodes are configured with dual 12-core processors, 12 – 4TB drives, and from 256 to 512 GB of memory.
Now that the Teradata Appliance for Hadoop 5 with Cloudera is officially available to all, we are proud to have brought more freedom of choice to our customers and to help accelerate their time to business value. Come by Teradata’s booth at Strata + Hadoop World and talk to us about why leading data driven companies are deploying a data-and-analytic-centric information management platform.
Chris Twogood is vice president of product and services marketing for Teradata Corporation. He is responsible for marketing Teradata products (database, utilities, and platform), Aster Products and Hadoop, as well as Teradata services (professional and customer services), plus technical field sales support teams. Twogood has twenty-five years of experience with extensive experience in the computer industry. He has specializing in data warehousing, decision support, customer management, and appliance platforms.
He started his career with NCR in retail Point of Sale solutions (POS), and then moved to AT&T to manage channel development and strategic partners. Then, Twogood joined Teradata where he managed strategy, application definition, marketing, product requirements/management, platform solutions, and product marketing.
Twogood holds a Bachelor of Science degree from California State University at Long Beach with an emphasis in marketing. He resides in San Diego.
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