How will SQL be used to manage and query data in increasingly complex data architectures?

SQL is still the dominant language for managing and querying data in complex and distributed data architectures. This is because SQL is a powerful and expressive language that can support a wide range of data types and workloads. Additionally, SQL is well-supported by a wide range of database vendors, making it easy to find a database that meets your specific needs.

Here are some ways that SQL is being used to manage and query data in increasingly complex and distributed data architectures:

Distributed SQL databases: Distributed SQL databases, such as CockroachDB and Google Cloud Spanner, provide a single logical database that is distributed across multiple physical nodes. This makes it possible to scale your database to handle large amounts of data and traffic. Distributed SQL databases also provide high availability and disaster recovery, making them ideal for mission-critical applications.
SQL-on-Hadoop: SQL-on-Hadoop tools, such as Apache Hive and Presto, allow you to query Hadoop data using SQL. This makes it possible to use SQL to analyze large datasets that are stored in Hadoop.
SQL federations: SQL federations allow you to query data from multiple heterogeneous data sources using SQL. This makes it possible to create a single view of your data, even if it is spread across different databases and systems.
In addition to these technologies, SQL vendors are also adding new features to SQL to support increasingly complex and distributed data architectures. For example, some SQL vendors are adding support for distributed transactions and geospatial data.

Here are some specific examples of how SQL is being used to manage and query data in increasingly complex and distributed data architectures:

Netflix: Netflix uses a distributed SQL database called Vitess to manage its user data and video streaming data. Vitess is a distributed MySQL database that can scale to handle the massive amount of data that Netflix generates.
Walmart: Walmart uses a SQL federation called Federation Server to query data from its various data sources, including Hadoop, Hive, and MySQL. Federation Server allows Walmart to create a single view of its data, even though it is spread across different systems.
Amazon: Amazon uses a distributed SQL database called Aurora to manage its customer data and transaction data. Aurora is a PostgreSQL-compatible database that is designed to be highly scalable and reliable.
Overall, SQL is a powerful and versatile language that can be used to manage and query data in increasingly complex and distributed data architectures. SQL vendors are constantly adding new features to SQL to make it even more powerful and flexible.