A total solution for high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine.

HPCMATEed Spark cluster solution powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. HPCMATE provides fully automated Spark cluster framework solution from data feeding, Real-time/Batch and Machine Learning Processing Cluster Framework.

Best for

• Fully automated Apache Spark framework for build, deployment, validation
• Write applications quickly in Java, Scala, Python, R, and SQL
• unified analytics engine for large-scale data processing, Combine SQL, streaming, and complex analytics