MapR Celebrates Four Year Anniversary of Apache Drill Delivering Self-Service SQL Analytics

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The MapR team has reason to celebrate; today we announce the four-year anniversary of the general availability of Apache Drill, the open-source distributed SQL query engine, integrated into the MapR Data Platform delivering fast and secure self-service BI SQL analytics at scale.

Drill was designed as the first schema-free SQL query engine built for Hadoop, NoSQL, and Cloud stores. It enables you (our customers, future customers, or anyone who finds the value of Drill) to get faster insights from all their data and all the data-types — whether the data is structured or semi-structured — all by using familiar SQL semantics and BI/Analytics tools. Drill continues to be widely recognized by industry experts as the next evolutionary phase of SQL that uniquely brings together performance without compromising flexibility. Drill has the ability to infer schema on the fly, without requiring a schema specification upfront. As a result, Drill continues to generate interest and gain popularity.

A few Milestones at a Glance:

Other highlights of Apache Drill's success on the MapR Data Platform include:

Contributor Support

While MapR continues to be a major innovation driver for Apache Drill, there are more than 170 individuals who have submitted more than 3,500 contributions that have grown the Apache Drill code base to more than 600,000 lines of code. The contributors come from companies such as Alibaba, Alipay, Cloudera, Intuit, Deutsche Bank, making it the industry SQL engine of choice on structured, semi-structured, and unstructured data formats in on-premises and cloud environments.

Use Cases

Apache Drill is being widely deployed in many Fortune 500 enterprises for self-service data exploration/data discovery use cases as well for high-performance BI/AdHoc analytics on large-scale datasets. Examples of use-case examples include security analytics, risk reporting, user analytics, claims analytics, customer 360, clickstream analytics as well as BI/Analytics on data lakes. The use cases often are for internal usage as well as user-facing analytics as a service application.

Modular Architecture

Customer interest in Drill in the last four years has been steadily increasing as a way to augment and in some cases replace an existing RDBMS and Data Warehouse systems. Drill's modular architecture allows customers to easily plugin customizations, which in turn easily allows querying of additional data formats, all using industry standard ANSI SQL.

Looking Back

A look back at Drill's four-year journey and accomplishments:

2015

  • Drill 1.0 is generally available after six months of successful Beta
  • Four revisions of Drill released - Drill 1.1.0 through 1.4.0
  • Major features - Full Hive support, more SQL constructs, improved handling of metadata

2016

  • Five revisions of Drill - Drill 1.5.0 through 1.9.0
  • Major features - Ability to launch Drill cluster as a YARN application, HBase support, native connector for Tableau, dynamic UDF's

2017

  • Three revisions of Drill - 1.10.0 through 1.12.0
  • Major Features - End to end enterprise-grade security with Kerberos, low latency operational queries with native secondary index integration with MapR database, native connectivity from Zeppelin notebooks, granular monitoring, ability to launch multiple Drill clusters

2018

2019

Quotes from customers and contributors

“Overall, Drill performs very fast as compared to the same queries running on Hive. So far I love Drill and want to use it with my all BI tools,”

-Irfan Zaidi, Big Data Architect at Baptist Health of South Florida.

“The core Drill team at MapR has been thrilled with the widespread support from engineers around the globe. They, like us, share the vision of what Drill can be and keep working to make Drill the industry's best SQL engine on structured, semi-structured and unstructured data formats,”

-Aman Sinha, Architect at MapR.

“Moving forward, the Apache Drill community's innovation agenda includes a cutting edge feature set such as resource management, automatic schema provisioning, the ability to launch Drill clusters from Kubernetes, a brand new Metastore concept, expanded statistics support, and numerous performance improvements. We are excited about the future and possibilities of Drill in the coming years.”

-Pritesh Maker, Vice President, Engineering at MapR.


This blog post was published June 07, 2019.
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