MapR announced today that our SQL-on-Hadoop solution earned the highest score for Hadoop/data warehouse interoperability. MapR was among six vendors invited to participate in Gigaom Research’s January 2015 report, “Sector Roadmap: Hadoop/Data Warehouse Interoperability.” One of the key factors for our top placement in this competitive evaluation was the integration powers of Apache Drill’s technology included in the MapR Distribution.
This report validates Apache Drill as a major advancement in data exploration given its schema flexibility, which makes it possible for you to immediately query complex data in native formats, such as schema-less data, nested data, and data with rapidly-evolving schemas, with minimal IT involvement. Since SQL queries can run directly on various file formats, live data can be explored as it’s coming in, versus the more IT-driven method of preparing and managing schemas and setting up ETL tasks. The other powerful integration feature of Apache Drill is the fact that it supports ANSI SQL, so you can easily leverage your SQL skills and use existing BI tools.
Once you gain the insight from new data, modeling and “schema-tizing” for repeatable analysis and reporting is hugely valuable. This can be done using Hive metastore or in relational best-of-breed solutions such as Teradata, which is why integration with existing technologies and standards is so critical in order to optimize your data architecture. Adding data discovery and exploration with tools like Apache Drill are additive and net-new capabilities and do not replace the tried and true methods of data governance, data warehousing, and business intelligence.
Gigaom Research’s Sector Roadmap report looked at SQL-on-Hadoop solution offerings from MapR, Cloudera, Hortonworks, Teradata, Oracle, and Pivotal. The report includes a detailed analysis of key usage scenarios made possible by these solutions, and the architectural difference between them.
The roadmap looked at six key Disruption Vectors:
- schema flexibility
- data engine interoperability
- pricing model
- enterprise manageability
- workload role optimization
- query engine maturity
Collectively, these Disruption Vectors measured how well each SQL-on-Hadoop solution facilitates Hadoop-data warehouse integration and how it does so with respect to emerging usage patterns.
Here’s how MapR scored in each disruption vector:
- Number indicates company’s relative strength across all vectors
- Size of ball indicates company’s relative strength along individual vector
Source: Gigaom Research
The full Gigaom Research Sector Roadmap: Hadoop/Data Warehouse Interoperability report can be accessed here.
We continue to see significant community momentum in Apache Drill and its capabilities. Be sure to keep up to date with Drill through the Apache Drill blog, which is updated regularly. To learn more about Drill or give it a try for yourself, check out the following resources:
- Download Drill here
- Download MapR Sandbox for Drill
- Top 10 Reasons for Using Apache Drill - Now as Part of MapR Distribution Including Hadoop
- A simple 10-minute tutorial
- Analyzing Yelp JSON Data with Apache Drill
- A more comprehensive Hadoop tutorial
If you have any questions, please ask them in the comments section below.