What Big Names Are Offering in Big Data

Loraine Lawson
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Why the Hoopla over Hadoop?

Hadoop in nine easy-to-understand facts.

Yesterday, I shared some of the big players in Big Data.


Today, I'm focusing on the big technology vendors that either are taking a unique approach or are using partnerships to break into the Big Data market. My goal here isn't to cover every company, but rather to give you an idea of what the major enterprise companies (and a few other big tech names) are doing to address Big Data:


Amazon Web Services. If you're looking for a cloud-based option, Amazon offers Elastic Map Reduce, which is a hosted, scalable Hadoop service. It also offers tools to help with analytics. Another Big Data option from Amazon: DynamoDB, a NoSQL database.


Google. Not surprisingly, Google offers another cloud-based approach to Big Data. Google's Big Data offerings are BigQuery - an analytical database - and the Prediction API, which is still an immature offering and has something to do with machine learning, according to Radar O'Reilly. Its cloud application hosting service, AppEngine, also offers a MapReduce facility.


HP Vertica. Last year, HP acquired Big Data pure-play Vertica. It's not a Hadoop solution, but it is a Big Data column-oriented analytics database, used by the likes of Zynga and Groupon. It does offer a Hadoop connector. There's not a lot about it in the trade press, but it totals $84 million of HP's $550 million in Big Data revenue.


Microsoft. Hortonworks is helping Microsoft develop its own Hadoop-based offering on Windows Server and Windows Azure, for a third cloud-based option. Radar O'Reilly recently published a detailed look at Microsoft's Big Data strategy if you'd like to learn more. Microsoft is thinking big picture on this one: Word is, Redmond plans to contribute its adaptations back to the Apache Hadoop project, which means anybody will be able to run a purely open source Hadoop on Windows.


Oracle. Oracle introduced its Big Data Appliance in January at the surprising low price point of $450,000 with 12 percent hardware and software maintenance, which works out to be $54,000. This solution uses the Cloudera distribution of Hadoop, plus Cloudera Manager and R.


SAP. SAP's approach to Big Data is to focus on integrating it with other tools, which, honestly, makes it difficult to describe. It offers SAP HANA for transactional data. For large data stores, like Hadoop, "SAP is entering this market through Sybase IQ, which has added significant Map-Reduce capabilities," according to this Forbes article, which offers a very detailed assessment of SAP's Big Data approach.


Teradata Aster. Teradata Aster comes in both the basic software platform and as an appliance. It includes both SQL and MapReduce analytic processing. (See yesterday's post for more on Teradata's Big Data plans.)


SAS is working on a solution that marries Hadoop Distributed File System (HDFS) with in-memory analytics.


If you'd like to learn more about other Big Data solutions, I recommend these articles:


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