Archivo de la categoría: MapR

Big Data, Database, Hadoop, MapR, News & Analysis, patents

MapR gets converged data platform patented

dataCalifornia-based open source big data specialist MapR Technologies has been granted patent protection for its technique for converging open source, enterprise storage, NoSQL and other event streams.

The United States Patent and Trademark Office recognised the detail differentiation of the Hadoop specialist’s work within the free, Java-based programming framework of Hadoop. Though the technology is derived from technology created by the open source oriented Apache Software Foundation, the patent office has judged that MapR’s performance, data protection, disaster recovery and multi-tenancy features merit a recognisable level of differentiation.

The key components of the patent claims include a design based on containers, self-contained autonomous units with their own operating system and app software. Containers can ring fence data against loss, optimise replication techniques and create a system that can cater for multiple node failures in a cluster.

Other vital components of the system are transactional read-write-update semantics with cluster-wide consistency, recovery techniques and update techniques. The recovery features can reconcile the divergence of replicated data after node failure, even while transactional updates are continuously being added. The update techniques allow for extreme variations of performance and scale while supporting familiar application programming interfaces (APIs).

MapR claims its Converged Data Platform allows clients to innovate with open source, provides a foundation for analytics (by converging all the data), creates enterprise grade reliability in one open source platform and makes instant, continuous data processing possible.

It’s the differentiation of the core with standard APIs that makes it stand out from other Apache projects, MapR claims. Meanwhile the system’s ability to use a single cluster, that can handle converged workloads, makes it easier to manage and secure, it claims.

“The patent details how our platform gives us an advantage in the big data market. Some of the most demanding enterprises in the world are solving their business challenges using MapR,” said Anil Gadre, MapR Technologies’ senior VP of product management.

Big Data, Data, Database, MapR, News & Analysis, Streams

MapR claims world’s first converged data platform with Streams

Navigating big dataApache Hadoop system specialist MapR Technologies claims it has invented a new system to make sense of all the disjointed streams of real time information flooding into big data platforms. The new MapR Streams system will, it says, blend everything from systems logs to sensors to social media feeds, whether it’s transactional or tracking data, and manage it all under one converged platform.

Stream is described as a stream processing tool that can handle real-time event handling and high scalability. When combined with other MapR offerings, it can harmonise existing storage data and NoSQL tools to create a converged data platform. This, it says, is the first of its kind in the cloud industry.

Starting from early 2016, when the technology becomes available, cloud operators can combine Streams with MapR-FS for storage and the MapR-DB in-Hadoop NoSQL database, to build a MapR Converged Data Platform. This will liberate users from having to monitor information from streams, file storage, databases and analytics, the vendor says.

Since it can handle billions of messages per second and join clusters from separate data centres across the globe, the tool could be of particular interested to cloud operators, according to Michael Brown, CTO at comScore. “Our system analyses over 65 billion new events a day, and MapR Streams is built to ingest and process these events in real time, opening the doors to a new level of product offerings for our customers,” he said.

While traditional workloads are being optimised, new workloads from the emerging IoT dataflows are presenting far greater challenges that need to be solved in a fraction of the time, claims MapR. The MapR Streams will help companies deal with the volume, variety and speed at which data has to be analysed while simplifying the multiple layers of hardware stacks, networking and data processing systems, according to MapR. Blending MapR Streams into a converged data system eliminates multiple siloes of data for streaming, analytics and traditional systems of record, MapR claimed.

MapR Streams supports standard application programming interfaces (APIs) and integrates with other popular stream processors like Spark Streaming, Storm, Flink and Apex. When available, the MapR Converged Data Platform will be offered as a free to use Community Edition to encourage developers to experiment.

administrators, Database, developers, Internet of Things, IoT, JSON, MapR, News & Analysis

MapR claims JSON IoT development breakthrough

Cloud databaseEnterprise software vendor MapR has unveiled plans to slash the workload of IoT developers and administrators by cutting the complexity of managing its NoSQL databases.

The key to this simplification, it says, is in more creative use of the JavaScript Object Notification (JSON) format, which it claims has the potential to make significant improvements in both database scalability and the analysis of the information they contain.

“We’re seeing big changes in the way applications are developed and how data is consumed,” said MapR’s chief marketing officer Jack Norris, “the underlying data format is the key to making information sharing easier.”

Bringing out the advantages of JSON makes administration easier, according to Norris, because users can make changes easily in a database built on documents. This in turn helps developers when they are planning applications, because it is easier to create a user friendly system. Tweaking JSON will benefit system builders in their own work too, Norris argued, since a document database can now be given enterprise grade scalability, reliability and integrated analytics.

The organisational improvements include the ability to personalise and deliver better online shopping experiences, reduce risk and prevent fraud in real-time, improve manufacturing efficiencies and cut costs. Savings will come from preventing cluster sprawl, eliminating data silos and lowering the cost of ownership of data management, claims MapR. Meanwhile it has promised a productivity dividend from continuous analytics of real-time data.

The MapR-DB supports the Open JSON Application Interface (OJAITM), which is designed to be a general purpose JSON access layer across databases, file systems and message streams, enabling a flexible and unified interface to work with big data, claims MapR.

The addition of a document database capacity extends the NoSQL MapR-DB to cover more types of unstructured business data, said one analyst. This could make it faster and easier to build big data applications, without the burden of shuffling data around first.

“MapR continues to build on the innovative data platform at the core of its Hadoop distribution,” said Nik Rouda, senior analyst at the Enterprise Strategy Group.