How will SQL evolve to support new data types and workloads, and spatial data?

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How will SQL evolve to support new data types workloads, and spatial data?

Alejandro Penzini Answered question October 30, 2023
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SQL is a mature language, but it is constantly evolving to meet the needs of new data types and workloads. Here are some ways that SQL is evolving to support new data types and workloads:

New data types: SQL vendors are adding new data types to support new kinds of data, such as JSON, XML, and graph data. For example, PostgreSQL has a JSONB data type that is specifically optimized for storing and querying JSON data.
Native support for new workloads: SQL vendors are also adding native support for new workloads, such as graph processing and time series analysis. For example, Microsoft SQL Server has a new temporal data type that makes it easy to store and query time-series data.
Extensions: SQL vendors are also adding extensions to SQL to support new workloads. For example, MySQL has a spatial extension that adds support for geospatial data.
In addition to these specific changes, SQL vendors are also working to make SQL more extensible. This will make it easier for developers to add support for new data types and workloads to SQL.

Here are some specific examples of how SQL is evolving to support new data types and workloads:

Graph data: Some SQL vendors, such as Neo4j and OrientDB, are specifically designed for working with graph data. These databases provide native support for graph queries and operations. Other SQL vendors, such as PostgreSQL and MySQL, are adding extensions to support graph data.
Time series data: Some SQL vendors, such as TimescaleDB and InfluxDB, are specifically designed for working with time series data. These databases provide native support for time series queries and operations. Other SQL vendors, such as Microsoft SQL Server and PostgreSQL, are adding data types and functions to support time series data.
Spatial data: Some SQL vendors, such as PostGIS and SpatiaLite, are specifically designed for working with spatial data. These databases provide native support for spatial queries and operations. Other SQL vendors, such as MySQL and Oracle Database, are adding extensions to support spatial data.
Overall, SQL is evolving to become a more versatile and powerful language that can support a wide range of data types and workloads. This is making SQL a more attractive option for developers who are working with new kinds of data and new applications.

Alejandro Penzini Answered question October 30, 2023
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