Apache Drill vs RESTHeart

Low-latency SQL queries;Dynamic queries on self-describing data in files (such as JSON, Parquet, text) and MapR-DB/HBase tables, without requiring metadata definitions in the Hive metastore.;ANSI SQL;Nested data support;Integration with Apache Hive (queries on Hive tables and views, support for all Hive file formats and Hive UDFs);BI/SQL tool integration using standard JDBC/ODBC drivers

Setup in minutes the lightweight and fast microservice with support for MongoDB and AWS DocumentDB; Available also as a Docker image; Built on standards, like HTTP, JSON, REST, JSON and JSON Schema; Read JSON documents with GET requests, specifying MongoDB queries and projection options; Deal with large result sets with pagination; Create, modify and delete JSON documents with POST, PUT, PATCH and DELETE requests; Use bulk requests to deal with multiple documents in one shot; Out-of-the-box User Authentication and Authorization; Store and serve binary data with GridFS support; Define and execute Aggregations, supporting both map-reduce and aggregation pipelines; Execute requests in multi-document ACID transactions; Access real-time data changes via Websocket Change Streams; Create dbs, collections and indexes with Data Model API; Validate requests with JSON Schema; Extend RESTHeart via Plugins: transform, check requests and responses; Keep data secure with authenticators and authorizers; Executes WebHooks after a request completes; Implement Web Services in minutes; Serve Static Resources (such as HTML, CSS, images and JavaScript); Define Relationships so that documents automatically include hyperlinks to referenced data; Forget about HTTP details with automatic support of Cross-origin resource sharing, Web Caching and HTTP ETag to avoid ghost writes; Navigate data with the embedded browser web app