Aster Data Deal Drives MapReduce Into Teradata's Strategy
The acquisition will advance graph analysis against clickstreams and social media messages. Competitors will respond on the "No SQL" and social network analytics fronts.
It was just a matter of time. Aster Data, one of the most innovative startups in the enterprise data warehousing (EDW) arena, is moving rapidly into the ranks of leading vendors in this hotly competitive space.
Teradata, one of the longtime EDW powerhouses, yesterday announced that it is acquiring San Carlos, California-based Aster Data. This $263 million all-cash deal, expected to close in the second quarter, will bring Aster Data's well-regarded brand, exceptional team, growing product portfolio, and sophisticated intellectual property (IP) into Teradata.
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For starters, the acquisition further substantiates several market trends that we called out in the recent Forrester Wave on EDW Platforms:
Vendor consolidation proceeds apace. The EDW market has largely consolidated, though startup activity remains strong. Customer demand for one-stop shopping has driven consolidation and demand for completely integrated appliance-based EDWs, and, increasingly, for cloud- and software-as-a-service (SaaS)-based access to the same functionality.
The past year has seen SAP acquire Sybase, IBM purchase Netezza, EMC buy Greenplum, HP announce its intention to absorb Vertica -- and now this latest bombshell deal. Clearly, Teradata -- the long-ago first mover in EDW appliances -- is acquiring Aster Data in part for a strong appliance-based offering of its nCluster platform, which is architected for modular scaling of MapReduce operations.
Cloud/SaaS EDWs come into the enterprise. Over the next two to three years, cloud/SaaS EDWs will gain greater enterprise adoption as a complement or outright replacement for appliance- and software-based EDWs. Already, Teradata stands out through its ability to offer the most mature and comprehensive range of cloud/SaaS-based EDW offerings on the market, while Aster Data has been one of the leading pure-plays with a predominant focus on cloud/SaaS deployments for Web 2.0, social media, and other hot new applications.
In this regard, the architectural synergies of Teradata and Aster Data are considerable. Both offer petabyte scale-out, shared-nothing, massively parallel processing, support elastic resource provisioning for mixed workloads in federated EDW deployments, and integrate with external Hadoop Distributed File System clusters for analytics against unstructured sources.
In addition, what Aster adds to Teradata's solution portfolio is an increasingly important cloud EDW capability: optimization of massively parallel "graph analysis" against clickstreams, social media messages, and other event data types. This functionality will prove invaluable in the new age of social commerce.
In-database analytics and transaction processing transform the EDW's roles. Increasingly, EDWs are deployed at the heart of the next-generation customer relationship management (CRM) environment, executing and integrating analytics and transactional computing functions to enable pervasive, next-best actions in multichannel customer service, sales, and marketing.
The current best-of-breed EDW platforms support analytics-driven multichannel CRM through features such as MapReduce, in-database function pushdown, embedded statistical algorithm libraries, predictive modeling integration, and mixed workload management. Both Teradata and Aster Data are especially strong in these areas. Teradata already has a strong multichannel campaign management portfolio, which it strengthened recently by acquiring Aprimo.
What Aster adds is the ability to support further scaling and acceleration of next-best actions by integrating both types of next-best-action workloads -- analytics and transaction processing -- in a unified cloud architecture. In this important new architectural paradigm, which Forrester calls the "analytic application server," Aster's closest competitor has been Oracle's Exadata platform. Clearly, Teradata now has an important new asset for fighting off this formidable rival.
Social media drive unstructured data and real-time architectures into the EDW. Marketing, sales, and customer service professionals everywhere integrate social media into their business-to-consumer customer-facing processes. A key application is social media analytic dashboards to monitor customer awareness, sentiment, and propensities in real time.
To address these requirements, and the convergence of in-database data mining and text analytics, both Teradata and Aster Data have incorporated support for unstructured sources, hybrid storage architectures, in-memory execution, distributed cache, and real-time processing into their architectures. In addition, both have partnered with SAS Institute and other advanced analytics vendors who provide the algorithm libraries to support high-volume low-latency mining of social-media-sourced customer intelligence from disparate sources.
What Aster brings to Teradata is one of the deepest libraries of MapReduce algorithms to bootstrap customer development and deployment of social media analytics in "Big Data" cloud EDWs. In addition, the acquisition will address what has increasingly become a Teradata competitive vulnerability: its ability to only offer customers a single, proprietary (albeit highly scalable and robust) database management system (DBMS) within its EDW portfolio.