5GSoftware Integrations

Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.

Enterprise search, observability, and security for the cloud. Quickly and easily find information, gain insights, and protect your technology investment whether you run on Amazon Web Services, Google Cloud, or Microsoft Azure. We handle the maintenance and upkeep, so you can focus on gaining the insights that help you run your business. Configuration and deployment are a breeze. Simple scaling, custom plugins, and architecture optimized for log and time series data are only a taste of what’s possible. Get the complete Elastic experience with features like machine learning, Canvas, APM, index lifecycle management, Elastic App Search, Elastic Workplace Search, and more — exclusively available here. Logging and metrics are just the start. Bring your diverse data together to address security, observability, and other critical use cases.

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark 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. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.