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Warehouse is purpose-built for JSON data

SonarW is a columnar data warehouse built especially to handle JSON data. It can support data warehousing for MongoDB systems and some data lakes.

SonarW, recently released by analytics developer jSonar, is a columnar data warehouse built especially to handle JSON data. It helps meet analytical workload needs for MongoDB operational systems, and can be deployed within Hadoop environments -- particularly those that might be described as "JSON data lakes."

Lexington, Mass.-based jSonar's software is intended to address the growing need to run deeper back-end analytics on data gathered during operations using NoSQL databases. Today, much of that gathered data takes the form of documents using JavaScript Object Notation (JSON), which allows for flexible data schemas in tune with the industry-wide push for agile development.

"The data world is going through a renaissance and a lot of that is happening around JSON," said Ron Bennatan, CEO and co-founder of jSonar. "JSON may be a format for a long time because it easily supports changes in data."

The changes in data structure happen now at a rapid pace -- one that sometimes tests the patience of business users reliant on SQL-centric OLTP databases and data warehouses. The complexity is reflected in schemas that are hard to change and projects that seem to take forever. "The reason why everything takes so long is that change with today's data warehouses requires a forklift upgrade to the schema," said Bennatan, who served as distinguished engineer at IBM after its 2009 purchase of Guardium, at which he served as CTO.

Despite benefits to building with little in the way of schemas, there are places in the process where some such data structure is useful. Bennatan said that SonarW can derive after-the-fact schemas by indexing all data as it spreads out to store in columns. "The software studies the structure and produces a metadata model," he said.

The software also supports multi-threading and Massively Parallel Processing, which is all done in JSON, said Bennatan. Working natively with the JSON format -- already popular in NoSQL operational databases -- will be similarly well-liked for analytical workloads, he said.

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