is one of my favorite destinations and I started contributing some articles there on how I think the industry should move on JSON and SQL. Here is a teaser:


How SQL Extensions are Helping SQL Adapt to Flexibility of JSON

It is clear that all types of databases are on boarding JSON. However there are varying levels of “native-ness” they can offer.

  • On the native-ness level, most native implementations are the new JSON based operational document databases — Couchbase, MongoDB, DocumentDB etc come with JSON documents as the data model and provide fast access to data natively taking JSON in and serving JSON out. Most provide SQL based languages to query (Couchbase Server N1QL and DocumentDB SQL) the data except MongoDB (see find() method).
  • Relational Databases are retrofitting JSON by using a data type much like XML. SQL Server, Oracle, MySQL, and Postgres all are following this path. The query language provides functions to manipulate JSON. They translate JSON in and out of their native data type — tables, columns and rows.
  • Even some columnar and key value databases like Cassandra, MapR-DB, Riak are on board with JSON. They are trying to extend their native models with a JSON cover on top, much like relational databases.
  • Aside from databases, many SQL based analytics languages like Drill, Hive, Spark and others also have extended their languages to process JSON.

It is clear JSON is popular as it is the de-facto serialization format. Here is how SQL is being extended to help process the flexiable natre of JSON…

Happy reading.



Posted by Cihan Biyikoglu, Director of Product Management, Couchbase

Cihan Biyikoglu is a director of product management at Couchbase, responsible for the Couchbase Server product. Cihan is a big data enthusiast who brings over twenty years of experience to Redis Labs’ product team. Cihan started his career as a C/C++ developer.

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