MapR and SAP share a common belief and vision about making big data analytics enterprise- ready, both at the platform and compute engine layer. In that regard, we are pleased to integrate and support SAP HANA Vora 1.3 and believe that it offers a complete solution for all types of big data analytic use cases.
Partners Blog Posts
There's one important question on everyone's mind these days: "With all this information at our disposal, how do we leverage it in more strategic ways?" The most effective way to guarantee high returns on the massive amounts of structured and unstructured information you generate and store is to make sure it is used by and shared with as many stakeholders as possible.
According to IDC, the big data market, including services such as analytics, is expected to reach nearly $50 billion by 2019. Luckily for Quantium, data is in its DNA. Australia’s largest analytics business is happily riding the coattails of the booming global big data industry.
MapR is pleased to support our partner Cisco with today’s UCS S-Series launch. The Cisco UCS S-Series consists of storage-optimized servers configured for scale-out storage (both Software Defined Storage and Web-Scale Storage with MapR).
MapR, Cisco, and SAP have been collaborating for years to help you gain insight from all of your data sources. Today, we’re excited to announce that Cisco has developed an appliance that includes the MapR Converged Data Platform for SAP HANA, making it much easier and faster for you to harness the power of big data.
In the world of data warehouses and data marts, OLAP analysis has existed for many years. Concepts like drill down, drill across and roll ups have allowed business analysts and users to easily access and analyze data across a variety of dimensions such as product, customers and regions.
The MapR Distribution including Hadoop is now available on the Azure Fast Start. This solution enables push button deployment of MapR on the Azure cloud infrastructure, providing you with the solutions to turn your big data into big money.
How times have changed—10-15 years ago, when you needed to store data for your application, it was likely structured data; the data fields were known ahead of time and didn’t change much.
As more organizations begin to deploy Spark in their production clusters, the need for fine-grained monitoring tools becomes paramount.
MapR is glad to partner with SAP and we are excited to see them bring lead-edge innovations to the market. We are thrilled today to talk about a new offering from SAP that along with the MapR data platform to help you better serve your customers and simplify how your business works.
How do you navigate the make vs. buy decisions today with multiple big data software vendors who have more offerings than ever? In this blog post, I’ll explore your choices when you have an existing product in market.
Every week, there are reports about new data breaches at organizations ranging from retailers to government agencies to, ahem, “dating services.” In fact, the theft of sensitive data costs global industry over $445 billion each year.
Organizations have struggled with critical performance and scalability shortcomings of conventional data integration for years, leading many to push heavy data integration workloads down to the data warehouse. As a result, core data integration experienced a shift from extract, transform, and load (ETL) to extract, load, and transform (ELT).
Today, a significant number of our customers are deploying the MapR Big Data platform in the cloud. This is not only true for development and test use cases, but also for many more production ones, especially those in the Internet of Everything (IoE) space.
The MapR Distribution including Hadoop is now available in a private IT sandbox environment on the Amazon Web Services (AWS) Test Drive. We’ve partnered with AWS to create this lab environment so that you can gain hands-on experience with Hadoop.
For the past several years, organizations have been struggling to figure out how to deal with all of the new data that is streaming in all around them. From smartphones to production line sensors, everything is generating data.
I’m writing to share some good news about the MapR Distribution on Amazon EMR. As of 4/6, version 4.0.2 of the MapR Distribution including Hadoop will be available for customers to deploy using Amazon EMR. Customers can quickly and easily use Amazon EMR to deploy and manage MapR, which features updated Apache projects - including YARN and Hive 0.13 - and takes advantage of new features, including promotable mirrors, that MapR has added to our differentiated MapR data platform.
With the turn of the century, the technological revolution, and the onset of social media, big data has become critical to our everyday lives. By enabling us to make advancements in finance, communications, medicine, and scientific research, it has helped us find, store, deliver, and analyze large volumes of distributed data. Most interesting, perhaps, is big data’s role in genomics and its ability to identify, map, and sequence hundreds of millions of strands of DNA.
A recent study published by Accenture and General Electric revealed that 87% of enterprises believe big data analytics will redefine the competitive landscape of their industries within the next three years. As big data analytics moves into the mainstream, we will see an increase in data-driven innovation across all major industries. So how do you identify the right analytics use cases for your business, and how do you get them deployed quickly?
I am excited to share some good news about the MapR Distribution on Amazon EMR. First, Amazon Web Services has added support for the latest generation Amazon EC2 instance families with the Community (M3), Enterprise (M5), and Enterprise Database (M7) editions of the MapR Distribution in Amazon EMR. This means that you can now create Amazon EMR clusters with the MapR Distribution using the M3, C3, R3, I2, and G2 instance families.
We are pleased to announce that MapR has entered into an expanded partnership agreement with Teradata to provide our best-in-class Hadoop distribution, support, and services as part of the Teradata Unified Data Architecture. MapR already has dozens of joint customers with Teradata across major industries who use both of our solutions. Now those customers benefit from even deeper technical integration and new options for support and services.
We are excited to announce that MapR has entered into a partnership agreement with Cisco to resell the MapR Distribution including Apache Hadoop. Together, Cisco and MapR are well positioned to help you unlock the power in your big data by offering a solution that features cost-effective management, increased agility, massive scalability, lower TCO, industry-leading performance, and end-to-end security.
In this blog series, we’re showcasing the top 10 reasons customers are turning to MapR in order to create new insights and optimize their data-driven strategies. Here’s reason #2: MapR provides world record performance for Hadoop.
When enterprise big data projects are successful, they can transform everything from operational efficiencies and product development to customer interactions and management processes. To help organizations glean the most value from their big data initiatives, CenturyLink Technology Solutions (formerly Savvis) recently announced a full suite of big data managed services, including MapR hosting and management.
In a new briefing, the 451 Group details MapR’s exciting past few months. MapR has continued to strive to expand our product to meet our customers needs in wherever computing environment they may have – in the cloud, on-premise or both. The Amazon and Google announcements serve to establish MapR as the emerging defacto standard for Hadoop.
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