Wilmington, DE, Aug. 30, 2021 (GLOBE NEWSWIRE) -- The Apache Drill Project announced the release of Apache® DrillTM v1.19, the schema-free Big Data SQL query engine for Apache Hadoop®, NoSQL, and Cloud storage.
"Drill 1.19 is our biggest release ever," said Charles Givre, Vice President of Apache Drill. "With an already short learning curve, Drill 1.19 makes it even easier for users to quickly query, analyze, and visualize data from disparate sources and complex data sets.”
An "SQL-on-Hadoop" engine, Apache Drill is easy to deploy, highly performant, able to quickly process trillions of records, and scalable from a single laptop to a 1000-node cluster. With its schema-free JSON model (the first distributed SQL query engine of its kind), Drill is able to query complex semi-structured data in situ without requiring users to define schemas or transform data. It provides plug-and-play integration with existing Hive and HBase deployments, and is extensible out-of-the-box to access multiple data sources, such as S3 and Apache HDFS, HBase, and Hive. Additionally, Drill can directly query data from REST APIs to include platforms like SalesForce and ServiceNow.
Drill supports the ANSI SQL 2003 standard syntax ecosystem as well as dozens of NoSQL databases and file systems, including Apache HBase, MongoDB, Elasticsearch, Cassandra, REST APIs, , HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, NAS, local files, and more. Drill leverages familiar BI tools (such as Apache Superset, Tableau, MicroStrategy, QlikView and Excel) as well as data virtualization and visualization tools, and runs interactive queries on Hive tables with different Hive metastores.
Apache Drill v1.19
Drill is designed from the ground up to support high-performance analysis on rapidly evolving data on modern Big Data applications. v1.19 reflects more than 100 changes, improvements, and new features that include:
- New Connectors for Apache Cassandra, Elasticsearch, and Splunk
- New Format Reader for XML without schemas
- Added Avro support for Kafka plugin
- Integrated password vault for secure credential storage
- Support for Linux ARM64 systems
- Added limit pushdowns for file systems, HTTP REST APIs and MongoDB
- Added streaming for Drill's REST API
- Integration with Apache Airflow
Developers, analysts, business users, and data scientists use Apache Drill for data exploration and analysis for its enterprise-grade reliability, security, and performance. Drill's flexibility and ease-of-use have attracted thousands of users that include Ant Group, Cardlytics, Cisco, Ericsson, Intuit, MicroStrategy, Qlik, Tableau, TIBCO, TransUnion, Twitter, National University of Singapore, and more.
"Individuals, businesses, and organizations of all types rely on Apache Drill's rich functionality," added Givre. "We invite everyone to participate in our user and developer lists as well as our Slack channel, and contribute to the project to build on our momentum and help improve the future experience for all Drill users."
Catch Apache Drill in action at ApacheCon@Home, taking place online 21-23 September 2021. For more information and to register, visit https://www.apachecon.com/ .
Availability and Oversight
Apache Drill software is released under the Apache License v2.0 and is overseen by a volunteer, self-selected team of active contributors to the project. A Project Management Committee (PMC) guides the Project's day-to-day operations, including community development and product releases.
About Apache Drill
Apache Drill is the Open Source, schema-free Big Data SQL query engine for Apache Hadoop, NoSQL, and Cloud storage. For more information, including documentation and ways to become involved with Apache Drill, visit http://drill.apache.org/ , https://twitter.com/ApacheDrill , and https://apache-drill.slack.com/ .
© The Apache Software Foundation. "Apache", "Drill", "Apache Drill", and "ApacheCon" are registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. All other brands and trademarks are the property of their respective owners.
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