What is SQL compatibility?

SQL compatibility measures how well a database or analytics engine conforms to SQL standards in areas like syntax, datatypes, functions, operators, and handling of nulls and three-valued logic. Higher compatibility allows easier migration from other SQL environments.

Core SQL elements like SELECT, JOIN, GROUP BY, aggregates should function similarly. Vendor specific SQL extensions may provide additional functionality if needed. Adhering closely to standard SQL helps limit lock-in.

For analytics engines like Apache Arrow DataFusion, SQL compatibility enables users to leverage existing SQL skills. It also simplifies migrating analytics workflows from traditional relational databases.

The query execution engine needs to handle standard SQL correctly. SQL with minimal proprietary extensions makes it easier to switch between analytical tools if needed. Standard SQL skills apply across compatible platforms.

What does it do/how does it work?

High SQL compatibility lets developers reuse SQL skills and code while limiting proprietary extensions. Standards compliance also aids interoperability between different systems.

ANSI SQL standard features are implemented in a compatible way. Data types, operators, functions behave predictably. Code portability is enhanced through consistent handling of nulls, dates, strings, identifiers, etc. Extensions build on top of standards.

Why is it important? Where is it used?

SQL skills are widely useful across many databases and systems. SQL compatibility allows easier migration between platforms, integration across systems, and code reusability.

High SQL compatibility is important for cloud analytics services, data lake environments, and data warehouses to attract users. It lowers switching costs compared to proprietary SQL dialects.

FAQ

What are some key areas of SQL compatibility?

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How is compatibility evolving?

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