YottaByte Me

New York, NY (PRWEB) April 07, 2015

JethroData, provider of the fastest SQL-on-Hadoop solution in the market, today announced the general availability of its flagship software. A major innovation delivering up to 100 times faster queries, JethroData’s unique indexing technology enables companies to harvest their Big Data at the speed of business. JethroData works with popular business intelligence (BI) solutions, including Qlik, Tableau and MicroStrategy to enable their users faster access to analyze their Big Data in Hadoop.

Unique Architecture Enables Truly Interactive Business Intelligence on Hadoop

JethroData’s unique vision combines search engine indexing technology with modern column store database design into a single solution. The resulting product addresses the growing business need for storing vast amounts of data while providing lightning-fast queries. JethroData’s breakthrough full-indexing technology enables BI users to enjoy interactive responses with Big Data. JethroData works seamlessly with any BI tool through a standard ODBC/JDBC interface, and is compatible with Hadoop distributions from Cloudera, Hortonworks, MapR and Amazon.

“Big Data users need to focus in on specific slices of diverse data sources which are useful for answering business questions without losing sight of the bigger picture. Qlik’s products are about building these specific apps downstream from the big data system,” said Les Bonney, COO at Qlik, a JethroData partner. “JethroData brings significant performance advances to accessing data in Hadoop, which combined with the Qlik associative experience, will enable our customers to continue discovering business value from their data – regardless of the variety or volume.”

“Our query performance on big data residing in Hadoop has improved dramatically since we started using JethroData,” said Slava Borodovsky, Senior Director of Business Intelligence at Fiverr and a JethroData customer since 2014. “This validates our initial belief that JethroData is the superior approach to other solutions we have tried. We are now implementing JethroData in our BI infrastructure to give us better insights into Fiverr users’ behavior.”

“Until today, customers using Hadoop benefited from its great scalability but had to sacrifice query performance,” said Eli Singer, JethroData’s co-founder and CEO. “This made Hadoop unsuitable for interactive BI, requiring companies to maintain an enterprise data warehouse (EDW) in parallel to their Hadoop infrastructure. The release of JethroData in GA now allows enterprises to benefit from both worlds: Big Data and lightning-fast querying, using one infrastructure: Hadoop.”

To learn more, and download a free trial of the JethroData product, please visit: http://jethrodata.com.

About JethroData

JethroData’s index-based SQL engine for big data delivers the fastest analytics on Hadoop and Amazon S3, enabling ad-hoc queries, live dashboards and interactive BI. JethroData customers enjoy the scalability of Hadoop with the performance of an analytical database, in one system. JethroData is headquartered in NYC and backed by world-class investors.

To learn more, go to: http://jethrodata.com.

Boulder, CO (PRWEB) November 10, 2014

SlamData, Inc., commercial developer of the SlamData open source project, announced the General Availability of their MongoDB BI/analytics solution.

Installers for the release are available from the SlamData website, or the project can be accessed on GitHub and built from source code. The project is licensed under the AGPL V3 license.

SlamData allows for unrestricted ad hoc queries on data stored in MongoDB. Unlike existing solutions, there is no need to relocate the data or write complicated code. SlamData is the only MongoDB analytics solution to offer 100% in database execution and does not stream data or require extensive data mapping or replication.

SlamSQL, the SQL dialect supported by SlamData, allows anyone to write standard SQL queries against data stored in MongoDB, even if that data is heavily nested or has non-uniform structure. SlamData includes a high-level graphical front-end that makes it simple to build and share reports that pull data from MongoDB.

According to SlamData CEO Jeff Carr, “SlamData is simpler to use and more powerful than any current MongoDB analytic solution. As a result we are seeing significant growth in our user base. Other solutions are limited in flexibility or takes days to set up and maintain.”

Continued Carr, “With SlamData you can literally be up and running queries in minutes. And unlike solutions that rely on streaming or other methods to move data, SlamData executes 100% in database and as a result supports very large amounts of data.”

SlamData tackles this issue directly using advanced mathematical extensions to relational algebra. SlamData’s approach allows full support for SQL queries executing directly on a MongoDB database (or replica set), and also the ability to support much more advanced queries than are possible in ANSI SQL.

The open source project already has hundreds of users. “Simple ad hoc analytics is an increasing issue for data-driven companies including Patheer, says Dennis Harris, Co-founder of Patheer, a company building on MongoDB. Continues Harris, “We have been searching for a solution that will allow us to analyze semi/un-structured data without complex MapReduce and other complicated ETL processes. SlamData has been a breath of fresh air as it allows us to analyze our semi/un structured data by just using simple SQL syntax and executes 100% in MongoDB. Other solutions we tried forced us to relocate our data to new data stores or cloud services which slowed us down and added complexity.”

The company’s patent-pending technology, invented by SlamData CTO John A. De Goes, is based on a formal generalization of 40-year-old relational algebra called MRA (“Murray”). De Goes is a well-known big data expert and founder of a previous TechStars big data startup.

MRA natively supports analytics on multi-structured data (anything from flat, homogeneous data, to multidimensional, heterogeneous data). Unlike all legacy RDBMS technology, there’s no need for ETL or transforming data to first-normal form, and MRA supports everything from simple sums and counts to statistical analysis.

About SlamData:

SlamData is the commercial entity supporting the SlamData open source project. The goal of the SlamData project is to make data stored in NoSQL databases accessible to a broader audience of users, without requiring extensive data replication or preparation as is the norm today. You can support the project by downloading here, or cloning or starring on Github here.

About Patheer:

Patheer is a data-driven analytics platform to engage, develop and retain employees. The Patheer platform encompasses both career research and career planning essentials for companies to help empower employees in the internal career advancement process.

Contact : Jeff Carr jeff(AT)slamdata.com : Twitter @slamdata