Solutions accelerate development of real-time security log analytics, time series analytics and genome sequencing applications
MapR Technologies, Inc., provider of the top-ranked distribution for Apache™ Hadoop®, today announced at Spark Summit the immediate availability of three new Apache Spark-based Quick Start Solutions for the MapR Distribution including Apache Hadoop. These solutions help customers take advantage of the rapid application development and in-memory processing capabilities of the Spark engine along with the enterprise-grade capabilities of the industry-leading Hadoop distribution. The solutions enable faster development of real-time big data applications on log data for security analytics, time-series data for real-time dashboards as well as to build clinical applications on human genome data.
The three Quick Start Solutions – Real-time Security Log Analytics, Time Series Analytics, and Genome Sequencing - will enable customers who are new to Spark to realize faster time-to-value with their implementations. The solutions can be customized to specific requirements and use cases with the help of world-class data scientists and engineers from MapR Professional Services, who have deep experience building Spark and Hadoop-based applications for customers.
“There has been tremendous response to the initial launch of our Quick Start Solutions since we introduced them earlier this year. We are seeing growing demand from our customers for Spark on Hadoop applications and have added Quick Start Solution offerings to meet our customers’ needs,” said Dave Jespersen, vice president of worldwide services, MapR Technologies. “Our Spark offerings have broad applicability and are designed to help our customers speed deployments and realize rapid returns on their investment.”
“We see widespread usage of Spark on Hadoop across different industries for a variety of use cases such as complex data pipelining, machine learning and real-time dash-boarding. The newly-added Quick Start Solutions from MapR provide a rapid ramp up to enable more customers to experience the power of Spark and its associated libraries on a production-grade Hadoop platform,” said Kavitha Mariappan, vice president of marketing at Databricks.
Details of New Spark-based Quick Start Solutions
Each new Quick Start Solution is tailored around a specific solution area and includes data ingest modules, professional services and a small Hadoop cluster that can easily be expanded based on the solution requirements. Details of the three new solutions include:
- Real-time Security Log Analytics combines the power of the highly reliable MapR Distribution with the Apache Spark stack to support real-time analysis of large volumes of security data, which can help in early detection of advanced persistent threats and unknown threats. The solution augments existing Security Information and Event Management (SIEM) solutions by providing cost-effective storage and processing for deep analytics and by predicting anomalous behavior within the environment to identify unknown threats.
- Time Series Analytics brings the reliable, top-ranked NoSQL database, MapR-DB, together with Apache Spark to support rapid ingestion and extraction of data along with real-time aggregation capabilities. The solution helps faster development of real-time monitoring applications and alert systems on various types of IoT-style data including time-series data coming from machines, sensors and devices.
- Genome Sequencing leverages Apache Hadoop and Spark for large-scale parallel processing of genome data providing lower latency compared to HPC and homegrown solutions. The solution reduces latency of converting a sequenced genome to clinically actionable information and supports flexibility and extensibility of various computational algorithms that can be utilized. The end result is faster development of downstream clinical applications at a lower overall cost compared to alternatives.
These three new Quick Start Solutions are available today from MapR worldwide.
MapR is showcasing its top-ranked, utility-grade Hadoop Distribution architected for real-time, data-centric enterprises this week at Spark Summit held at the Hilton Union Square in San Francisco, CA in booth # B2.