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Aster Data Systems

Aster Data is a proven leader in big data management and big data analysis for data-driven applications. Aster Data's nCluster is the first MPP data warehouse architecture that allows applications to be fully embedded within the database engine to enable ultra-fast, deep analysis of massive data sets. Aster Data's unique applications-within approach allows application logic to exist and execute with the data itself. Termed a Massively Parallel Data-Application Server, Aster Data�s solution effectively utilizes Aster's patent-pending SQL-MapReduce together with parallelized data processing and applications to address the big data challenge.

Companies using Aster Data include Coremetrics, MySpace, comScore, Akamai, Full Tilt Poker, and ShareThis. Aster Data is headquartered in San Carlos, California and is backed by Sequoia Capital, JAFCO Ventures, IVP, and Cambrian Ventures, as well as industry visionaries including David Cheriton, Ron Conway, and Rajeev Motwani.

Our Website: http://www.asterdata.com


Latest Content From Aster Data Systems

Whitepaper: 10 Reasons to Combine Storage and Analytics

by Aster Data SystemsAug 12, 2010

The era of big data management and deep analysis of massive amounts of data is opening new opportunities for significant competitive differentiation using advanced analytics.

There are ten strong reasons why competitive organizations are turning to new data management solutions to handle their growing data volumes and evolving analytic needs.

Download this checklist to learn more...


Whitepaper: Aster Data nCluster MPP Data Warehouse Datasheet

by Aster Data SystemsNov 04, 2009

Big Data applications demand richer, deeper data processing at ultra-fast speeds, massive but cost-effective scaling and the ability to seamlessly manage diverse workloads. From applications like fraud detection, to customer intelligence, to trending and forecasting, to scenario modeling, to customer personalization and targeting, to click stream analysis �- it is evident that enabling fast, deep processing of very large data sets can have a material impact on the business.

Aster Data�s nCluster is the first MPP data warehouse architecture that allows applications to be fully embedded with the database engine to enable ultra-fast, deep analysis of massive data sets. Termed a �Massively Parallel Data-Application Server,� Aster Data�s solution uses SQL-MapReduce with parallelized data processing and applications to address the big data challenge. Aster Data nCluster is available in three product lines, with the same massively parallel data-application server at the heart of each architecture:

Software-only: Aster Data nCluster
Cloud-based: Aster Data nCluster Cloud Edition
Appliance: Aster Data MapReduce Data Warehouse Appliance

Aster Data�s solution is the first massively parallel data-application server that uses Aster Data�s unique Applications-Within� approach. Applications-Within places application and analytics logic where data natively resides to speed analysis of large data sets. Data processing and applications are fully parallelized and run on low-cost commodity hardware. Aster Data�s solution Aster Data�s patent-pending SQL-MapReduce which enables rapid application development and reusability.


Whitepaper: Beyond Reporting: Requirements for Large-Scale Analytics

by Aster Data SystemsSep 23, 2009

Are you one of those organizations that is eager to move beyond the delivery of basic reporting capabilities?

Do you want to empower business analysts�who sit at the intersection of data, process, and math�to create data-driven applications that deliver bottom-line insights from massive volumes of data?

To apply analytics against large volumes of data, organizations need a purpose-built analytics platform that runs on a massively parallel processing environment and supports custom-built analytical programs that can be invoked via SQL. In addition, the analytic platform should enable IT departments to create sandboxes in the corporate database that give analysts free reign to add their own data and run high-performance analytics without impeding performance of other users on the system.

Read this TDWI report to understand what solutions are available in today�s market and how Aster Data is helping companies use SQL+MapReduce intelligently to fulfilling their Big Data Warehouse needs.


Whitepaper: Massive But Agile: Best Practices for Scaling the Next-Generation Enterprise Data Warehouse

by Aster Data SystemsAug 27, 2009

Information and knowledge management (I&KM) professionals continue to expand the scale, scope, and deployment roles for their enterprise data warehouse (EDW) investments. Today�s most demanding EDW environments support petabytes of aggregated data, trillions of records, thousands of concurrent users and queries, complex mixed-query workloads, subsecond latencies, and continuous, high-volume data loading. Information managers are adopting EDW best practices that push the scalability and performance envelope without sacrificing the agility to optimize this critical infrastructure to ever-changing analytic workloads.