The Top 7 Big Data Products In 2016

      

As data continues to rapidly grow, so do expectations on how to analyze it faster. Organizations are faced with lots of options these days. Unstructured Data is taking the information sector by storm and many companies are struggling to keep up. It is also advisable to note that the Big Data industry is maturing to the point where there are now established markets for the various categories of products and services, which make up the industry. Here is a list of a few Big Data applications that will help your company capture, analyze and, cash in on Big Data.

1)  MongoDB 3.0:

MongoDB is a leading NoSQL database, one of a wave of such products that position themselves as alternatives to the relational database management systems, including Oracle and Microsoft SQL Server that is core to many data centers today.

Earlier this year MongoDB launched MongoDB 3.0, which the New York Company trumpeted as shifting the database market "into [the] post-relational era." The new release sports new highly flexible storage architecture, based on technology from MongoDB's earlier Wired Tiger acquisition, and significant performance and scalability enhancements.

Also new was MongoDB Ops Manager, an application that database administrators and IT operations managers use to manage MongoDB deployments and reduce operational overhead costs by as much as 95 percent, 

2) Tableau 9.0:

Tableau launched this major release of its visual analysis software in April with faster performance and a new "analytics-in-the flow" capability that lets users stay focused on their analytical tasks rather than writing new calculations or preparing data. The application's Smart Maps are faster and more responsive while the new auto data preparation feature helps clean up messy data.

Seattle-based Tableau redesigned both the on premise Tableau Server and hosted Tableau Online from the ground up to make the systems more scalable, extensible and resilient, according to the company.

Tableau Online 9.0 has more data connection options, including the ability to connect directly to MySQL, Postgres and SQL Server on cloud-based platforms such as Amazon Relational Database Service and Windows Azure. And a new Tableau Online Sync feature keeps on premise data fresh for cloud analytics tools.

3) Qlik Sense 2.0:

Qlik's original (and still best-selling) product is its ClickView data visualization software. But last year the company debuted Qlik Sense, the vendor's more powerful "self-service" business analytics system that gives users more freedom to create their own analytical charts and visualizations.

Qlik Sense is something of a business analytics paradigm shift because it pushes more responsibility to business users and changes the role of IT. In April the company launched Qlik Sense 2.0, a major upgrade of the software that lets users pull data from disparate sources throughout an organization into a single analytical application. The software also can collect information from external syndicated sources and combine it with internal operational data for analysis

4) Kyvos Insights:

Kyvos Insights, which emerged from stealth mode in June, at the same time debuted its big data analytics software that can glean insights from huge volumes of corporate data.

Hadoop, the open-source platform that's becoming a standard for corporate big data systems, has been widely deployed for collecting and managing huge volumes of data. But businesses have struggled to find the best way to provide analysts and everyday business users with access to that data and derive value from it.

Kyvos's product is an OLAP (online analytical processing) application that supports multidimensional analytics on Hadoop. The software, according to the Los Gatos, Calif.-based company, can handle structured and unstructured Hadoop data "at any scale and granularity" and provide users with the ability to visualize and analyze big data interactively.

5) Couchbase N1QL:

SQL is the standard language for developing applications that access data in relational databases and it is used by millions of developers around the world. In June NoSQL database developer Couchbase, Mountain View, Calif., introduced N1QL (pronounced "nickel"), a programming language that developers with SQL expertise can use to build enterprise web, mobile and Internet-of-Things applications that run on the Couchbase Server.

Couchbase and other NoSQL database companies position their software as an alternative to relational database systems. Getting developers and ISVs to build apps for NoSQL databases is key to expanding their adoption. N1QL leverages SQL constructs, making it familiar to SQL developers, while extending the SQL syntax to support the Counchbase Server's JSON data modeling architecture.

6) Cloudera:

Cloudera recently launched Cloudera Enterprise 4.0 Big Data management platform, as well as the fourth-generation of the company’s distribution of the Apache Hadoop software known as CDH4.

The new release of Cloudera Enterprise includes an update to Cloudera Manager with new tools for deploying and managing Hadoop systems, improved management automation of large-scale clusters, and easier integration with a broader range of management tools and data sources.

The CDH4 release offers new high-availability features that eliminate the single point of failure of the Hadoop Distributed File System, increased security that allows more sensitive data to be stored in CDH, and the ability to run multiple data processing frameworks on the same Hadoop cluster.

7) Datameer:

Datameer is launching Datameer 2.0, a new release of its Big Data analytics software that combines data integration, analytics and visualization into a single package with a spreadsheet interface. While Datameer 1.0 was offered only in an enterprise edition, 2.0 adds workgroup and desktop editions to the Datameer lineup.

The release includes the new Business Infographics Designer for graphics and data visualization design control. The software is built on HTML5 and sports an enhanced user interface, offers support for additional data sources including Facebook and Twitter, and provides improved integration with the Hive data warehouse system for Hadoop