MapR Launches Spark-Based Quick Start Solutions for Hadoop
Solutions accelerate development of real-time security log analytics, time series analytics, and genome sequencing applications.
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MapR Technologies, Inc., a Apache Hadoop distribution provider, announced 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 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 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.
“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 dashboarding. 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 known threats.
- Time Series Analytics brings the reliable NoSQL database, MapR-DB, together with Apache Spark to support rapid ingestion and extraction of data along with real-time aggregation capabilities. The solution enables 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.
For more information, visit https://www.mapr.com/.