Which tool is described as an open-source, in-memory structured query language (SQL) query engine?

Apache Presto is accurately described as an open-source, in-memory structured query language (SQL) query engine. It was designed specifically to handle large amounts of data and to execute fast analytical queries across various data sources. Presto allows users to run SQL queries over large datasets that reside in different locations, including Hadoop, AWS S3, and other data types, and it does so with the ability to query data quickly in real-time.

Being an in-memory engine, Presto optimizes query execution performance by keeping data in memory, which reduces the need for disk I/O operations and allows for faster data processing. This capability is particularly beneficial for interactive and ad-hoc analysis, making it a preferred choice for analytics workloads that require low latency.

Other options like Hadoop and Apache Hive are more focused on distributed data storage and processing, with Hive specifically using a different approach to SQL-like querying by converting SQL queries into MapReduce jobs, which are typically slower than Presto's in-memory execution. Amazon Athena, while it utilizes Presto, is a serverless service focused on querying data stored in S3 rather than being a standalone query engine itself. Thus, Presto stands out as the tool that meets the criteria laid out in the question.