Here are some new and emerging SQL features and trends:
JSON support: Many databases now support JSON, a lightweight data-interchange format. This makes it easier to store and query JSON data in SQL databases.
Graph databases: Graph databases are a type of database that is designed to store and query graph data. Graph databases are becoming increasingly popular for applications such as social network analysis and fraud detection.
SQL on non-relational databases: SQL is being extended to support non-relational databases, such as NoSQL databases. This makes it possible to use SQL to query data that is stored in a variety of different database types.
SQL for machine learning: SQL is being used to develop new machine learning algorithms and to make existing machine learning algorithms more efficient. For example, SQL can be used to train and deploy machine learning models in real time.
Here are some specific examples of new and emerging SQL features:
Window functions: Window functions allow you to perform calculations on a subset of the data in a table. This can be useful for tasks such as calculating running totals and ranking rows.
Common table expressions (CTEs): CTEs allow you to define temporary named result sets that can be used in a SELECT, INSERT, UPDATE, or DELETE statement. This can help to simplify complex queries.
MERGE: The MERGE statement allows you to insert, update, and delete data in a single statement. This can be more efficient than using multiple INSERT, UPDATE, and DELETE statements.
JSONPath: JSONPath is a query language for JSON data. It is now supported by many SQL databases, which makes it easier to query JSON data in SQL.
These are just a few examples of the new and emerging SQL features and trends. SQL is a constantly evolving language, and new features and trends are being developed all the time. By staying up-to-date on the latest SQL features and trends, you can improve the performance and efficiency of your database applications.