When working with BigData & IoT systems we often feel the need for a CommonQuery Language. The platform specific languages are often harder to integratewith and require longer adoption time. To fill this gap many NoSql (Not-only-Sql) vendors are building SQL layers fortheir platforms. It is worth exploring the driving forces behind this trend,how it fits in your BigData stacks and how we can adopt it in our favoritetools. However building SQL engine from scratch is a daunting job andframeworks like Apache Calcite can help you with the heavy lifting. Calciteallow you to integrate SQL parser, cost-based optimizer, and JDBC with yourbig data system. Calcite has been used to empower many Big-Data platforms such as Hive, Spark,Drill Phoenix to name some. I will walk you through the process of building a SQL access layer for ApacheGeode (In-Memory Data Grid). I will share my experience, pitfalls andtechnical consideration like balancing between the SQL/RDBMS semantics and thedesign choices and limitations of the data system. Hopefully this will enable you to add SQL capabilities to your prefered NoSQLdata system. ❯ It will be interesting to see what happens if an established NoSQL databasedecides to implement a reasonably standard SQL; the only predictable outcomefor such an eventuality is plenty of argument. \- NoSQL Distilled, MartinFowler - 2012 The Relational Databases (RDBMS) are an essential component of the computingecosystem. Yet in the past decade we have witnessed a wave of alternative datamanagement technologies often branded as NoSQL and BigData - an ambiguous andlacking prescriptive definition names. To understand the NoSQL/BigData "movement" one need to understand the forcesfueling it: * The rise of Internet (Web, Mobile, IoT...) leading to Data {Volume, Velocity and Variety} challenges * Object-relational impedance mismatch * Cloud computing - Infrastructure Automation and Elasticity * Shift from Integration to Application databases * Data-Value vs. Storage-Cost Economics Shift The various approaches in addressing those challenges have led to a multitudeof over 150 commercially supported NoSQL/BigData platforms. Such diversity means that an organization will adopt a mixture of data storagetechnologies for handling different circumstances (Polyglot Persistence). How does an organization integrate the mix of data technologies? To fill the gap many NoSql/BigData vendors are (or are considering) buildingSQL and SQL-based layers for their platforms. It is worth exploring the driving forces behind this trend ...