IBM Netezza is #22 in Top 23 Big Data platforms

Last updated: January 02, 2020
IBM Netezza appliances - expert integrated systems with built in expertise, integration by design and a simplified user experience. With simple deployment, out-of-the-box optimization, no tuning and minimal on-going maintenance, the IBM PureData System for Analytics has the industry’s fastest time-to-value and lowest total-cost-of-ownership.

Positions in ratings


#22 in Top 23 Big Data platforms

Alternatives


The best alternatives to IBM Netezza are: Teradata, Hadoop



Latest news about IBM Netezza


2014. IBM adds Netezza analytics as a service to its cloud



IBM announced a bunch of new cloud data services to IBM Cloud, including an intelligent data-preparation tool DataWorks, an in-memory analytic database Netezza-powered dashDB and even a local version of a historically cloud-based database Cloudant. It’s an impressive and in some cases even unique set of capabilities that complements the work IBM has been pushing with its Bluemix platform. In particular, with the dashDB, IBM joins Amazon Web Services, Google and Microsoft with a homegrown analytic service built atop columnar database technology.




2014. The Netezza team is back with Big Data startup Cazena



Starup Cazena, that just launched with $8 million funding, promises to simplify big data for large companies. The company is leaning pretty heavily on its founding team’s experience building data warehouse specialist Netezza (which was acquired by IBM in 2010) earlier this century: Cazena CEO Prat Moghe (pictured above) was a senior vice president at Netezza, while Netezza founder Jit Saxena and longtime Netezza CEO Jim Baum sit on the company’s board. They say that large companies are confused about the technologies they need to deploy. They don’t necessarily know when and where things like Hadoop, NoSQL, Spark, Elasticsearch come into play, and they certainly don’t know how to turn them into a functional “data lake” like some vendors are pitching. Cazena wants to make big data less about infrastructure and more about applications, and it wants to use the cloud to do it.