NoSQL Analytics Startup Precog Comes out of Beta, Announces Three New Market Solutions

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Precog, the leading vendor for NoSQL analytics, today announced the general availability of its analytics platform for non-relational data. The announcement comes approximately 6 months after Precog launched its public beta.

Precog, the leading vendor for NoSQL analytics, today announced the general availability of its analytics platform for non-relational data. The announcement comes approximately 6 months after Precog launched its public beta.

With the GA release, Precog has formalized pricing for its cloud offering, which starts at $500 on the low-end (for storing and analyzing up to 10GB on SSDs), and reaches $5000 on the high-end (for up to 500 GB). In addition, the company has launched two new deployment options, including a virtual appliance and a hardware appliance, both designed with the needs of Enterprise customers, and which range in price from $5000 to $60000.

According to company founder and CEO John A. De Goes, more than 1,300 companies have signed up for beta accounts since October. De Goes states, “Our rapid growth is fueled by the explosion of non-relational data. To use legacy analytics solutions on NoSQL data, you have to first make the data relational through costly, time-consuming, fragile transformation processes. Companies are fed up with this incessant pounding of a square peg into a round hole.”

Continued De Goes, “Even when you normalize your non-relational data, you can’t do much with something like a tweet inside a relational database except count it. Companies are moving beyond sums and counts. They want to ask deeper questions across all of their data, whether it’s well-structured tabular data, or messy unstructured data.”

While positioned as a general-purpose, advanced analytics platform for non-relational data (including social media data, log files, clickstream data, JSON data, and sensor data), Precog has announced three highly targeted solutions built on top its core technology, each available as a cloud offering, a hardware appliance, or a virtual appliance.

Precog Social Insights is a social media analytics solution designed to provide companies with analytical insight into sentiment, demographics, and trends for brands and products. Social Insights offers direct integration with the Twitter firehose, and includes ad hoc reporting based on a variety of techniques in Natural Language Processing (NLP), including sentiment analysis, concept extraction, and taxonomies. The appliance integrates with a company’s own internal data sources, such as sales and marketing data, and with external data sources.

Precog Web Insights is a web analytics solution designed for ad hoc analysis of website and web app interaction data, and tying these interactions back to sales, marketing activities, and other company data. Precog Web Insights integrates the open source analytics package Scribe Analytics to provide comprehensive website analytics without the need for IT or engineering resources.

Precog Embedded Insights is an analytics and reporting solution designed for integration into a company’s existing application, to provide the users of that application with analytics and reporting based on any data managed by the application, together with other data sets that may need to be correlated with application data.

Precog has filed multiple patents covering its technology. The company’s technology is based on a generalization of 40 year old relational algebra to handle multi-structured data (ranging from flat, homogeneous data, to multidimensional, heterogeneous data), and advanced analytics.

This generalized algebra, which Precog calls QIL, is capable of natively handling non-relational data and performing the full spectrum of analytics, from simple sums and counts to statistical analysis. In contrast, RDBMS technology is based relational algebra, which is capable only of computing very simple analytics on flat, homogeneous data.

Precog is the first technology vendor to offer a solution that allows companies which are leveraging non-relational (NoSQL) operational data stores to perform analytics directly on their data, without the need for transformations (ETL)

NoSQL databases such as MongoDB, Riak, Couchbase, and Cloudant have experienced a surge in popularity over the past few years, with companies of all sizes adopting the technologies to store NoSQL data. As operational databases, these solutions are not designed to perform analytics, and do not offer analytic capabilities beyond simple aggregation. This forces many companies to transform their NoSQL data into tabular form, or to dump the data into Hadoop and use MapReduce to analyze it.

“With Precog,” De Goes says, “the days of ETL are over. Now more than ever, companies have exploding volumes of non-relational data, and they want to perform deeper analysis across that data. With Precog, they can natively and deeply analyze all their data, whether relational or not.”

Precog’s customer list includes SnapEngage, CollegeMiner, University of Massachusetts, Flixmaster, SITA, Novawise, and a number of Enterprises.

Jeff A. Carr, COO

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