In recent years, the rise of modern, non-relational datastores such as NoSQL databases, Hadoop and cloud storage has made it easier for developers to build and scale applications. However, these datastores make it harder for business users and analysts to analyze the data. In many cases, data engineers must develop complex ETL pipelines, loading the data into a centralized relational database or SQL-on-Hadoop environment.

Apache Drill is an open source, in-memory, columnar SQL execution engine. It enables users and BI tools to execute large-scale, interactive SQL queries against one more datastores. Drill supports NoSQL databases (eg, MongoDB, HBase, Kudu), search (eg, Elasticsearch, Solr), file systems (eg, HDFS, NAS), cloud storage (eg, Amazon S3, Azure Blob Storage) and relational database (eg, MySQL, Oracle). Users can run queries on a single system or join data between multiple systems. For example, a user can join log files in Elasticsearch with user profiles in MySQL or even an Excel spreadsheet.

In this talk we provide an overview of Apache Drill, and explain how to use it to query data in one or more datastores, with a particular emphasis on modern, non-relational datastores. In addition, we provide a live demo that shows how to use BI tools such as Tableau with datastores such HDFS, MongoDB and Elasticsearch.