Hadoop vs MapR


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Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.
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MapR
The MapR Distribution for Apache Hadoop provides organizations with an enterprise-grade distributed data platform to reliably store and process big data. MapR packages a broad set of Apache open source ecosystem projects enabling batch, interactive, or real-time applications. The data platform and the projects are all tied together through an advanced management console to monitor and manage the entire system.
Hadoop vs MapR in our news:


2019 - HPE acquires big data platform MapR



Hewlett Packard Enterprises has acquired MapR Technologies, the distributor of a Hadoop-based data analytics platform. The deal includes MapR’s technology, intellectual property, and domain expertise in AI, machine learning, and analytics data management. The MapR portfolio will bolster HPE’s existing big data offerings, which includes the BlueData software it acquired in November. BlueData’s software delivers a container-based approach for spinning up and managing Hadoop, Spark, and other environments on bare metal, cloud, or hybrid platforms. The MapR platform provides a number of capabilities for running distributed applications. The software exposes storage APIs for e S3 API, to go along with APIs for HDFS, POISX, NFS, and Kafka.

2015 - MapR tries to separate from Hadoop - a new advantage over Apache Cassandra



MapR is one of several companies built on the open source Hadoop platform, and as such it has a bit of competition in the space. In an effort to create some separation from its better heeled rivals, it announced a new product called MapR Streams. This new product takes a constant stream of data like feeding consumer data to advertisers to create custom offers or distributing health data to medical professionals to tailor medication or treatment options — all of this in near real-time. Streams let customers share data sources with people or machines that need to make use of that information in a subscription-style model. A maintenance program could subscribe to the data coming from the shop floor of a manufacturer and learn about usage, production, bottlenecks and wear and tear, or IT could subscribe to a data stream with log information looking for anomalies that signal maintenance issues or a security breach.

2015 - MapR adds Apache Drill to its Hadoop distribution



MapR announced that its Hadoop distribution now ships with Apache Drill - an open source, low latency SQL query engine for Hadoop and NoSQL. Its promise is that it makes it easier for end users to interact with data from both legacy transactional systems and new data sources, such as Internet of Things (IoT) sensors, web click-streams and other semi-structured data, along with support for popular business intelligence (BI) and data visualization tools. Apache Drill 1.0, which is now included in MapR’s distro, is free for the taking. So should a competitor, like Hortonworks, who has at least one contributor on the project, find it extremely valuable, they can engineer it into their distro as well.

2015 - MapR revamps its Hadoop platform with more real-time analytics. Beware Cloudera



The latest release of MapR enterprise-grade distributed Hadoop data platform is built for the real time, data-centric enterprise. It leverages table replication features designed to extend access to “big and fast” data enabling multiple instances to be updated in different locations, with all the changes synchronized across them. Reacting to business as it happens with the right offer is a must. Wrong offers are not only missed opportunities but put enough of them together and they could threaten a company’s viability. That’s one of the reasons why some enterprises are ditching their RDBMS and going with MapR. It offers both a top-rated NoSQL database and Hadoop in nicely bundled solution. MapR, unlike its competitors Hortonworks and Cloudera, is a software company whose aim is to make big data plug and play.

2014 - MapR partners with Teradata to reach enterprise customers



The last independent Hadoop provider MapR and big data analytics provider Teradata announced that they will work together to integrate and co-develop their joint products and to create a unified go to market strategy. Teradata will also be able to resell MapR software, professional services, and provide customer support. In other words, Teradata will be the face of MapR to enterprises who use, or want to use, both technologies. Until recently Teradata partnered most closely with Hortonworks, but now it’s sharing love and its analytic market leadership with all three providers. Similarly, earlier this week, HP announced Vertica for SQL on Hadoop, which allows users to access and explore data residing in any of the three primary Hadoop distros — Hortonworks, MapR, Cloudera.

2014 - HP plugs the Vertica analytics platform into Hadoop - a new advantage over Amazon Redshift



HP announced Vertica for SQL on Hadoop. Vertica is an analytics platform that enables customers to access and explore data residing in any of the three primary Hadoop distros — Hortonworks, MapR, Cloudera — or any combination thereof. Large companies are often using all three kinds of Hadoop because they don’t know which will be dominant. HP is one of the first big vendors to say “any flavor of Hadoop will do” by taking action, though it has invested $50 million in Hortonworks which is, at present, the flavor of Hadoop inside HAVEn, its analytics stack. HP’s announcement centers not only around its interoperability, but also its power on data stored in a data lake, enterprise data hub, whatever you want to call it. HP now provides a seamless way to explore and exploit value in data that’s stored on the Hadoop Distributed File System (HDFS). The power, speed, and scalability of HP Vertica with the ease with which Hadoop lassos big data might persuade reticent managers to come out from underneath their desks and take big data on.

2014 - Cloudera helps to manage Hadoop on Amazon cloud



Hadoop vendor Cloudera announced a new product called Director that will make it easier for customers to manage their Hadoop clusters on the Amazon Web Services cloud. Senior Director of Product Marketing Clarke Patterson acknowledged that has not been easy to date while still maintaining the breadth of capabilities. Although there’s no difference between the cloud version and the on-premises version of the software, he added, the Director interface is designed to be self-service and includes cloud-specific capabilities such as instance-tracking so administrators can keep an eye on whose cloud instances are costing what.