MapR unveils platform for IoT analytics at the edge

At Strata + Hadoop World in San Jose, Calif., Tuesday, MapR Technologies took the wraps off a new small footprint edition of its Converged Data Platform geared for capturing, processing and analyzing data from internet of things (IoT) devices at the edge.

MapR Edge, designed to work in conjunction with the core MapR Converged Enterprise Edition, provides local processing, aggregation of insights at the core and the ability to then push intelligence back to the edge.

“You can think of it as a mini-cluster that’s close to the source and can do analytics where the data resides, but then send data back to the core,” says Dale Kim, senior director, Industry Solution, at MapR Technologies.

“The use cases for IoT continue to grow, and in many situations, the volume of data generated at the edge requires bandwidth levels that overwhelm the available resources,” Jason Stamper, analyst, Data Platforms & Analytics, 451 Research, added in a statement. “MapR is pushing the computation and analysis of IoT data close to the sources, allowing more efficient and faster decision-making locally, while also allowing subsets of the data to be reliably transported to a central analytics deployment.

Many core IoT use cases, like vehicles and oil rigs, operate in conditions with limited connectivity, making sending massive streams of data back to a central analytics core impractical. The idea behind MapR Edge is to capture and process most of that data at the edge, where the data is created, then send summarized data back to the core, which then aggregates that summarized data from hundreds or thousands of edge IoT devices.

MapR Technologies calls this concept “Act Locally, Learn Globally,” which means that IoT applications leverage local data from numerous sources for constructing machine learning or deep learning models with global knowledge. These models are then deployed to the edge to enable real-time decisions based on local events.

To make it work, MapR Edge integrates a globally distributed elastic data fabric that supports distributed processing and geo-distributed database applications.

MapR Edge capabilities include:

• Distributed data aggregation. Provides high-speed local processing, useful for location-restricted or sensitive data such as personally identifiable information (PII), and consolidates IoT data from edge sites.
• Bandwidth awareness. Adjusts throughput from the edge to the cloud and/or data center, even with environments that are only occasionally connected.
• Global data plane. Provides global view of all distributed clusters in a single namespace, simplifying application development and deployment.
• Converged analytics. Combines operational decision-making with real-time analysis of data at the edge.
• Unified security. End-to-end IoT security provides authentication, authorization and access control from the edge to the central clusters. MapR Edge also delivers secure encryption on the wire for data communicated between the edge and the main data center.
• Standards based. MapR Edge adheres to standards including POSIX and HDFS API for file access, ANSI SQL for querying, Kafka API for event streams and HBase and OJAI API for NoSQL database.
• Enterprise-grade reliability. Delivers a reliable computing environment to tolerate multiple hardware failures that can occur in remote, isolated deployments.

MapR Edge deployments are intended to be used in conjunction with central analytics and operational clusters running on the MapR Converged Enterprise Edition. It is available in 3-5 node configurations and optimized for small form-factor commodity hardware like the Intel NUC Mini PC. MapR Edge deployments can store up to 50TB per cluster.

Jack Norris, senior vice president, Data and Applications, MapR Technologies, notes that MapR has all the data protection capabilities of MapR Converged Data Platform.

“There’s redundancy built in,” he says. “High, availability, self-healing, all the capabilities of the MapR technology are extended to the edge device.”

“Our customers have pioneered the use of big data and want to continuously stay ahead of the competition,” Ted Dunning, chief application architect, MapR Technologies, said in a statement Tuesday. “Working in real-time at the edge presents unique challenges and opportunities to digitally transform an organization. Our customers want to act locally, but learn globally, and MapR Edge lets them do that more efficiently, reliably, securely and with much more impact.”

This story, “MapR unveils platform for IoT analytics at the edge” was originally published by CIO.

Source: InfoWorld Big Data

MongoDB adds free tier and migration utility to cloud service

NoSQL database specialist MongoDB unveiled a new free tier for its MongoDB Atlas database-as-a-service (DaaS) offering on Tuesday. The company also released a utility to support live migration of data to MongoDB Atlas, whether that data is on-premise or in the cloud.

“Since we first introduced MongoDB to the community in 2009, we have been laser-focused on one thing—building a technology that gets out of the way of developers and makes them more productive,” Eliot Horowitz, CTO and co-founder of MongoDB, said in a statement Tuesday. “Now, with these updates to MongoDB Atlas, we’re tearing down more of the barriers that stand between developers and their giant ideas.”

The MongoDB Atlas service now offers a free cluster with 512 MB of storage, with nodes distributed to ensure high availability. Data is secured by default with authorization via SCRAM-SHA-1, TLS/SSL encryption for data traveling over networks and encrypted storage volumes for data at rest.

The new MongoMirror migration utility is designed to help users who are already running MongoDB to seamlessly pull data from their existing deployments and push it into MongoDB Atlas. The company says it will work with any existing MongoDB replica set running MongoDB 3.0 or higher. A hosted version of the live migration tool will soon be available in MongoDB Atlas.

MongoDB Atlas was engineered by the same team that built MongoDB, and the company says it incorporates the best practices of real world use cases, from startups to Fortune 500 companies. MongoDB launched it in June 2016 and says thousands of organizations around the world are already making use of the service, including companies like eHarmony and Thermo Fisher Scientific. Now it hopes to reduce barriers to adoption even more by making it free to get started and offering a way to seamlessly migrate existing workloads.

“The move to MongoDB Atlas has been a great win for us,” said James Mullaney, Technical Director at UK-based learning and performance R&D specialist HT2 Labs, which recently migrated its education data platform from a third-party MongoDB service provider to MongoDB Atlas to reduce costs and better scale its business. “We were able to scale to five times as much data while keeping database costs flat. Also, protecting our data assets is critical as we handle massive amounts of private education data. The fact that MongoDB’s native security features are baked into the Atlas platform made our migration decision that much easier.”

This story, “MongoDB adds free tier and migration utility to cloud service” was originally published by CIO.

Source: InfoWorld Big Data

MapR and Outscale partner on big data PaaS

At the Big Data Paris event in Paris, France, today, MapR Technologies and French enterprise-class cloud provider Outscale announced that they have joined forces to provide a big data platform-as-a-service (PaaS) offering built on the MapR Converged Data Platform.

Outscale will provide the new premium cloud service in Europe, North America and Asia and says it will provide customers with a cost-effective and flexible platform to support their big data journey — from initial proof of concept to prototype and application deployment, all with unlimited scalability.

“We are proud to offer MapR as the core technology to power our big data as a platform service because it enables our customers to spin up a full complete, multi-TB data platform in the cloud in a matter of minutes,” David Chassan, chief product officer, Outscale, said in a statement today. “We’ve worked on other solutions for big data, but found that MapR was the only one with the stability, scale and functionality that meets the needs of our enterprise customers and VARs.”

No expertise needed

Outscale says its new Big Data PaaS is designed to be simple to use in the cloud, and offers the entire MapR Converged Data Platform to provide fast access to data stored in files, databases and event streams for performing real-time analysis on business critical, operational applications. The service allows customers to test and deploy cloud-based applications on any size cluster, accessing open APIs including HDFS, Spark, Drill and POSIX NFS without the need for extensive professional service expertise in big data.

“Outscale is one of the leading cloud providers in France because of their strong expertise,” Yann Aubry, area vice president, Northern & Western Europe, MapR Technologies, said in a statement Monday. “With MapR at the core of their cloud platform, they quickly provide their customers with managed access to a converged data platform including the key big data technologies today. We are pleased to work with Outscale to deliver a technologically advanced cloud platform.”

Knocking down data silos

MapR Technologies introduced its Converged Data Platform in December 2015 as part of an effort to tear down the new data silos brought about by the scattershot proliferation of new analytics tools and the consumerization of enterprise software.

The MapR Converged Data Platform brings together the MapR Distribution, including Apache Hadoop, MapR-DB and MapR Streams (its global even stream system, which allows organizations to continuously collect, analyze and act on streaming data). It integrates file, database, stream processing and analytics to support data-driven applications.

This story, ” MapR and Outscale partner on big data PaaS” was originally published by CIO.

Source: InfoWorld Big Data

SAP adds new enterprise information management

SAP yesterday renewed its enterprise information management (EIM) portfolio with a series of updates aimed at helping organizations better manage, govern and strategically use and control their data assets.

“By effectively managing enterprise data to deliver trusted, complete and relevant information, organizations can ensure data is always actionable to gain business insight and drive innovation,” says Philip On, vice president of Product Marketing at SAP.

The additions to the EIM portfolio are intended to provide customers with enhanced support and connectivity for big data sources, improved data stewardship and metadata management capabilities and a pay-as-you-go cloud data quality service, he adds.

The updates to the EIM portfolio include the following features:

• SAP Data Services. Providing extended support and connectivity for integrating and loading large and diverse data types, SAP Data Services includes a data extraction capability for fast data transfer from Google BigQuery to data processing systems like Hadoop, SAP HANA Vora, SAP IQ, SAP HANA and other cloud storage. Other enhancements include optimizing data extraction from a HIVE table using Spark and new connectivity support for Amazon Redshift and Apache Cassandra.
• SAP Information Steward. The latest version helps speed data resolution issues with better usability, policy and workflow processes. You can immediately view and share data quality scorecards across devices without having to log into the application. You can also more easily access information policies while viewing rules, scorecards, metadata and terms to immediately verify compliance. New information policy web services allow policies outside of the application to be viewed anywhere such as corporate portals. Finally, new and enhanced metadata management capabilities provide data stewards and IT users a way to quickly search metadata and conduct more meaningful metadata discovery.
• SAP Agile Data Preparation. To improve collaboration capabilities between business users and data stewards, SAP Agile Data Preparation focuses on the bridge between agile business data mash-ups and central corporate governance. It allows you to share, export and import rules between different worksheets or between different data domains. The rules are shared through a central and managed repository as well as through the capability to import or export the rules using flat files. New data remediation capabilities were added allowing you to change the values of a given cell by just double clicking it, add a new column and populate with relevant data values, or add or remove records in a single action.
• SAP HANA smart data integration and smart data quality. The latest release of the SAP HANA platform features new performance and connectivity functionality to deliver faster, more robust real-time replication, bulk/batch data movement, data virtualization and data quality through one common user interface.
• SAP Data Quality Management microservices. This new cloud-based offering is available as a beta on SAP HANA Cloud Platform, developer edition. It’s a pay-as-you-go cloud-based service that ensures clean data by providing data validation and enrichment for addresses and geocodes within any application or environment.

“As organizations are moving to the cloud and digital business, the data foundation is so important,” On says. “It’s not just having the data, but having the right data. We want to give them a suite of solutions that truly allow them to deliver information excellence from the beginning to the end.”

On says SAP Data Quality Management microservices will be available later in the first quarter. The other offerings are all immediately available.

This story, “SAP adds new enterprise information management” was originally published by CIO.

Source: InfoWorld Big Data

MapR shows off enterprise-grade Spark distribution

At Spark Summit in San Francisco, Calif., this week, Hadoop distribution vendor MapR Technologies announced a new enterprise-grade Apache Spark distribution.

The new distribution, available now in both MapR Converged Community Edition and MapR Converged Enterprise Edition, includes the complete Spark stack, patented features from MapR and key open source projects that complement Spark.

“We’ve built this new distribution to make it easier for customers that leverage the power of Spark for their big data initiatives,” Anoop Dawar, vice president, Product Management, MapR Technologies, said in a statement yesterday. “We’ve seen significant growth of customers deploying Spark as their primary compute engine. We believe this gives our customers a converged compute and storage engine for batch, analytics and real-time processing that helps build and deploy applications rapidly.”

Spark catching fire

“ESG research shows Apache Spark adoption is poised to grow quickly, with 16 percent of businesses already in production and another 47 percent very interested in implementing Spark,” Nik Rouda, senior analyst with Enterprise Strategy Group, added in a statement Monday. “As such, Spark will power the next wave of big data. Yet enterprises will demand a robust platform to meet their operational requirements. MapR is helping to accelerate Spark by addressing this need.”