Orchestrate Big Data Analytics, ETL and Machine Learning
As modern scientific and engineering problems grow in complexity, the computation time and memory requirements increase and parallel computing becomes a necessity. Proactive Big Data Automation is a packaged solution to run and govern end-to-end Big Data and ML processes. ProActive integrates with de-facto standards in scientific and engineering environments.
Seamlessly parallelize your scientific models and programs from your favorite interactive environment (R Language, Matlab, Scilab). Use Spark and Hadoop platforms from ProActive.
We know that a single language cannot fit for every use case, calling for interoperability between multiple languages and services. Create a workflow of multidisciplinary tasks.
Adapt your infrastructure to your business. Proactive provide strong resources policies to federate multi, hybrid private & public cloud and connect elastic nodes to pay-as-you go
Enable business line users to access the cloud capacity through a user-friendly & powerful interface. Translate business needs and processes into expressive workflows and execute them at scale.
Proactive continually create ready-to-use tasks, in particular in big data to let our user create big data workflows easily and take benefit of ProActive Workflow and Scheduling governance features:
Distributed R environment for quantitative metagenomics platform and statistical analysis. more...
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Orchestration tools become more and more relevant to connect services, applications, multiple databases, compute over multi-clouds, custom analytics, automate and control processes. more...
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In this white paper, we will introduce the state of the art of big data processing: from parallel processing with the two main types of parallelisms, to several famous big data processing platforms such as Hadoop, Spark and YARN, and some Stream processing platforms like Spark Streaming, S4, Storm, Flink, etc. more...
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