Drill supports standard SQL (aka ANSI SQL). In addition, it features several extensions that help with complex data, such as the KVGEN and FLATTEN functions. For more details, refer to the SQL Reference.
No, The Drill can query data in-situ.
Apache Drill is a Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage and it allows us to explore, visualize and query different datasets without having to fix to a schema using ETL and so on.
Apache Drill is also Analyse the multi-structured and nested data in non-relational data stores directly without restricting any data.
Apache Drill is the first distributed SQL query engine and it contains the schema free JSON model and its looks like -
The Apache Drill is very useful for those professionals that already working with SQL databases and BI tools like Pentaho, Tableau, and Qlikview.
Also Apache Drill supports to -
Drill’s main focused on non-relational data stores, including Hadoop, NoSQL and cloud storage.
The following datastores are -
Hive is a batch processing framework most suitable for long-running jobs. For data exploration and BI, Drill provides a much better experience than Hive.
In addition, Drill is not limited to Hadoop. For example, it can query NoSQL databases (eg, MongoDB, HBase) and cloud storage (eg, Amazon S3, Google Cloud Storage, Azure Blob Storage, Swift).
Drill uses a decentralized metadata model and relies on its storage plugins to provide metadata. There is a storage plugin associated with each data source that is supported by Drill.
The name of the table in a query tells Drill where to get the data:
SELECT * FROM dfs1.root.`/my/log/files/`;
SELECT * FROM dfs2.root.`/home/john/log.json`;
SELECT * FROM mongodb1.website.users;
SELECT * FROM hive1.logs.frontend;
SELECT * FROM hbase1.events.clicks;
The Spark SQL only supports a subset of SQL but Apache Drill supports ANSI SQL.
Querying data in Spark SQL with help of languages like Java, Scala or Python but Apache Drill querying data with helps of MySQL or Oracle.