MapR announced the release of MapR 5.0, along with new auto-provisioning templates for data lake deployment, interactive SQL data exploration, and operational analytics at Hadoop Summit.

Version 5.0 of the MapR Hadoop distribution adds a new Views feature for the newly released Apache Drill 1.1 for agile data governance, and granular access controls for better unstructured file security. MapR 5.0 also includes “real-time data transport” for real-time search and data replication integrated with Elasticsearch, along with support for Apache Spark 1.3, including data frames and YARN 2.7 with a new Docker container executor.

Jack Norris, CMO of MapR, said MapR 5.0 is designed to extend Hadoop’s capabilities to real-time applications.

“We’re seeing a whole new class of flexible applications that give a whole lot of power to developers,” he said. “With [MapR 5.0], they’re free to choose between different methods for accessing and manipulating data in their application, but be assured their data protection, synchronization and data availability is the same.”

MapR’s new auto-provisioning templates reduce complexity in distributing Hadoop services by selecting optimal layouts, with “rack awareness” to automatically distribute services across failure domains, and to execute “health checks” on data lakes and the Hadoop distribution as a whole.

Hortonworks Data Platform 2.3 released
Hortonworks has released version 2.3 of the Hortonworks Data Platform (HDP), its open-source enterprise Hadoop platform. Version 2.3 adds Hortonworks SmartSense, a proactive Big Data monitoring service for large clusters, and enhancements to data encryption and authorization through Apache Ranger and Apache Knox.

(Related: Data Governance Initiative expands the Hadoop ecosystem)

Apache Atlas, a new incubator project developed through the Data Governance Initiative, adds a scalable metadata service, SQL metrics, and a UI for data search. Additional functionality in HDP 2.3 includes:

  • A new Apache Hive user view running on Apache Ambari to write, run and debug queries
  • A Data Frame API that enhances Apache Spark on YARN through machine-learning algorithms for feature-rich Spark applications
  • Web interface for forms-based creation of Apache Falcon data feeds and pipeline processing

Pentaho 5.4 released with Spark support, new APIs and integrations
Pentaho, now an official subsidiary of Hitachi Data Systems, released Pentaho 5.4 with orchestration for Apache Spark jobs, new APIs for embedded enterprise analytics, and integrations with Amazon Elastic MapReduce and SAP HANA. Pentaho 6.0 is expected to be released later this year.

Cloudwick launches Cloudwick Insights
Open-source Big Data integration software provider Cloudwick has rolled out a new Cloudwick Insights service at Hadoop Summit to assess Hadoop and Spark jobs by CPU, RAM, disk I/O and network utilization using Pepperdata. The service is designed to optimize real-time Hadoop performance.

Datameer and Tableau announce Big Data analytics and visualization connector
Big Data platform Datameer and business analytics provider Tableau have announced a new technology connector combining their respective solutions into a Hadoop analytics and visualization tool. Developers leveraging the solution will be provided with Datameer’s spreadsheet data interface through Tableau Desktop or Tableau Server for data visualization reporting.

Teradata launches Teradata RainStor, Teradata Loom 2.5 and Presto support
Big Data analytics provider Teradata made a variety of product announcements at Hadoop Summit. The company announced the launch of Teradata RainStor for archived SQL-based data analytics, Teradata Loom 2.5 for data lake security, and enterprise support for Facebook’s open-source Presto SQL query engine.

Arcadia Data unveils visual analytics and BI platform
Big Data business intelligence company Arcadia Data announced the launch of Arcadia Instant, a Big Data platform for sharing visualizations of granular data for BI insights. The company also announced US$11.5 million in Series A funding.