Bigstep announced that MapR is now available as part of the company’s big data platform-as-a-service. The Bigstep platform empowers organizations to effortlessly set up and manage big data architectures within a high-performance, highly secure and scalable bare metal environment. It is specifically built for big data workloads and provides improved performance for Hadoop, NoSQL and analytical DBs, search and analytics engines.
Companies building big data ecosystems are looking for tools that are easy to deploy and deliver fast results,” said Flaviu Radulescu, president and CTO, Bigstep. “We are now offering MapR as part of our big data platform so users have the ability to choose which Hadoop distributions and big data apps make the most sense for their businesses.”
MapR on Bigstep’s platform is one of the most extensive high-availability (HA) Hadoop distributions currently available. Its unique architecture makes it a reliable and fast solution for big data. Key features include record-breaking data processing power, an infinitely-scalable file system, high availability, disaster recovery setup and one-click setup in a high-performance bare metal environment.
We are pleased to now offer the MapR Converged Data Platform through Bigstep,” said Xavier Guerin, vice president, EMEA Business Development, MapR Technologies. “We continue to expand our partnerships and provide the most cloud options on the market for organizations interested in deploying a powerful platform for handling a wide range of real-time global data applications. Our customers have realized tremendous business value from the unparalleled performance, reliability, data protection, disaster recovery and multi-tenancy features we bring to the cloud.”
In addition, MapR on the Bigstep platform supports a wide selection of Hadoop applications so businesses with varying use cases and resources can rely on a single, easy to use solution from beginning to end.
Use Cases Include:
- Real-Time Stream Processing: MapR provides a simplified, publish-subscribe model for real-time stream computation using Storm or Spark Streaming. Data feeds can be written directly to the MapR platform, which allows for less overhead and a shorter app chain.
- Large-Scale Distributed Datasets: Low latency interactive query capability, hierarchical data structures and schema discovery make MapR on the Bigstep platform perfect for working with large-scale distributed datasets. It supports NoSQL, Hadoop and traditional RDBMS.
- Predictive Analytics, Full Search & Discovery: Gather trend data, search Hadoop data directly or index standard files with no conversion or transformation needed. Content and results are highly available, automatically compressed, and can be protected using snapshots and mirroring.
- Security & Risk Management: Analyze real-time data from network or other security devices, process application log data preemptively or use pattern and anomaly recognition capabilities to improve security and reduce unnecessary risk.
We selected Bigstep as our cloud platform provider because of its ease of use, speed and commitment to integrating the best big data tools and Hadoop distributions, such as MapR,” said Anthony Kalinde, Big Data Engineer, Dharmic Data AS. “The company allows us to experiment with different environments before making a commitment and has helped us build a solid foundation on which we can rapidly scale, iterate and deploy our solutions into production.”
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