Aster Data, which provides data management and data processing platform for big data analytic applications, today announced the 
delivery of over 30 ready-to-use advanced analytic packages and more than 1,000 MapReduce-ready functions to enable rapid development of rich analytic applications on big data sets.
The solution is a massively parallel database with an integrated analytics engine that leverages the MapReduce framework for large-scale data processing and couples SQL with MapReduce.
The expanded suite of pre-packaged SQL-MapReduce and MapReduce-ready functions accelerates the ability to build rich analytic applications that process terabytes to petabytes of data. [Disclosure: Aster Data, San Carlos, Calif., is a sponsor of BriefingsDirect podcasts.]
We have found that analytics that previously took weeks to months of SQL coding can now be built in days with richer analytic power than what is possible with SQL alone.
Traditional data management platforms and analytic solutions do not scale to big data volumes and restrict business insight to views that only represent a sample of data, which can lead to undiscovered patterns, restricted analysis and missed critical events. MapReduce is emerging as a parallel data processing standard, but often requires extensive learning time and specialized programming skills.
Coupling the SQL language with MapReduce eliminates the need to learn MapReduce programming or parallel programming concepts. Other benefits of this coupling include:
- Making MapReduce applications usable by anyone with a SQL skill-set.
- Enabling rich analytic applications to be built in days due to the simplicity of SQL-MapReduce and Aster Data’s suite of pre-built analytic functions.
- Delivering ultra-high performance on big data, achieved by embedding 100 percent of the analytics processing in-database, eliminating data movement.
- Automatically parallelizing both the data and application processing with SQL-MapReduce for extremely high performance on large data sets.
New functions
Aster Data also announced today a significant expansion in the library of MapReduce-ready functions available in Aster Data nCluster. The Aster Data nPath function is only one example of more than 1,000 functions now delivered through over 40 packages available with the Aster Data Analytic Foundation for Aster Data nCluster 4.5 and above.
These new functions cover a wide range of advanced analytic use cases from graph analysis to statistical analysis to predictive analytics, that bring extremely high value business functions out of the box that accelerate application development. Examples include:
- Text Analysis: Allows customers to “tokenize” count and position or count the occurrences of words as well as track the positions of words/multi-word phrases.
- Cluster Analysis: Includes segmentation techniques, like k-Means, which groups data into naturally occurring clusters.
- Utilities: Includes high value data transformation computations. For example developers can now simply unpack and pack nested data as well as anti-select, or allow the return of all columns except for those that are specified.
Aster also revealed new partners that are working closely with Aster Data’s data-analytics server, nCluster, to simplify development of highly-advanced and interactive analytic applications that process extremely large data volumes. Partners using SQL-MapReduce for rich analytics include Cobi Systems, Ermas Consulting, and Impetus Technologies.
Amiya Mansingh of Cobi Systems said, “There’s no question that Aster Data’s solution and SQL-MapReduce offers a powerful, yet easy-to-use framework to build rich, high performance applications on big data sets. We have found that analytics that previously took weeks to months of SQL coding can now be built in days with richer analytic power than what is possible with SQL alone. ”
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