What is Apache Drill?
Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel.
Apache Drill is a tool in the Database Tools category of a tech stack.
Who uses Apache Drill?
64 developers on StackShare have stated that they use Apache Drill.
Apache Drill Integrations
Pros of Apache Drill
NoSQL and Hadoop
Lightning speed and simplicity in face of data jungle
Well documented for fast install
SQL interface to multiple datasources
Nested Data support
Read Structured and unstructured data
V1.10 released - https://drill.apache.org/
Jobs that mention Apache Drill as a desired skillset
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Apache Drill's Features
- 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
Apache Drill Alternatives & Comparisons
What are some alternatives to Apache Drill?
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Distributed SQL Query Engine for Big Data
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
It is an open source framework for building databases and data management systems. It includes a SQL parser, an API for building expressions in relational algebra, and a query planning engine
Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.