Presto and SparkSQL are SQL interfaces to many different datasources, including Hive and Impala, but also any SQL database such as Postgres/Redis/etc, and many other types of databases, such as Cassandra and Redis; the SQL tools can query all these different types of databases with a unified SQL interface, and even do joins across them.
The difference between Presto and SparkSQL is that Presto is run on a multi-tenant cluster with automatic resource allocation. SparkSQL jobs tend to have to be allocated with a specific resource allocation ahead of time. This makes Presto is (in my experience) a little more user-friendly. On the other hand, SparkSQL has better support for writing data to different datasources, whereas Presto pretty much only supports collecting results from a client or writing data into Hive.
Presto and SparkSQL are SQL interfaces to many different datasources, including Hive and Impala, but also any SQL database such as Postgres/Redis/etc, and many other types of databases, such as Cassandra and Redis; the SQL tools can query all these different types of databases with a unified SQL interface, and even do joins across them.
The difference between Presto and SparkSQL is that Presto is run on a multi-tenant cluster with automatic resource allocation. SparkSQL jobs tend to have to be allocated with a specific resource allocation ahead of time. This makes Presto is (in my experience) a little more user-friendly. On the other hand, SparkSQL has better support for writing data to different datasources, whereas Presto pretty much only supports collecting results from a client or writing data into Hive.