Impetus Technologies’ visual big data analytics platform for Apache Spark available on the AWS Marketplace

Impetus Technologies, a big data software products and services company, announced Monday that StreamAnalytix is now available on the Amazon Web Services (AWS) Marketplace. StreamAnalytix makes the real-time enterprise possible and radically changes how business is done by empowering organizations to act on data as it originates.

Used by numerous companies, StreamAnalytix is an enterprise-grade platform designed to simplify and enhance the use of Apache Spark – increasingly the de facto standard for stream processing and machine learning applications. StreamAnalytix offers an intuitive visual interface that enables you to rapidly build and operationalize Apache Spark applications for end to end data processing, from data ingestion, data preparation, to advanced analytics and machine learning.

StreamAnalytix on AWS provides you the flexibility to work with any number of Spark nodes in a pay per use model. It is completely AWS optimized and supports deployment via cloud formation templates and is available on several different EC2 instance options, that can be chosen depending on the end user needs.

StreamAnalytix is available in two tiers− option 1 is a free to use, single node version that offers you a full range of data processing and analytics functionality to build, test and run Apache Spark applications on any single node. Option 2 is the full-scale enterprise edition that enables use of multiple Spark clusters, with no limit to the number of connected nodes.

Some of the many technical features associated with StreamAnalytix include end to end data processing with Apache Spark, a unified platform for data ingestion, data cleansing, blending, enrichment and transformation, advanced analytics and machine learning, action triggers, and data visualization. Users benefit from an array of drag-and-drop operators in an intuitive visual development environment. StreamAnalytix also makes it easy to introduce custom logic or write their own functionality in the language of choice, including Java, Python, Scala and SQL.

StreamAnalytix includes built-in connectors for Apache Kafka, Amazon S3, Elasticsearch, Apache HBase and Apache Hive. It also fully supports data formats, like JSON, CSV, AVRO and Apache Parquet. The platform makes it easy to build, train, calibrate, deploy and monitor machine learning models on both batch and real-time data, with use of built-in operators like Spark MLlib, Spark ML, PMML, H2O and TensorFlow. StreamAnalytix fully supports Apache Spark streaming, Apache Spark 2.2 and Apache Hadoop 2.7.3.

Data scientists, developers, business analysts and DevOps specialists excel with the extensive data manipulation capabilities inherent in StreamAnalytix. The integrated visual development environment (IDE) and drag-and-drop functionality makes it easy to create Spark pipelines and applications that enable both Spark experts as well enthusiasts to build enterprise grade big data applications for a range of use cases.

Some of these include the ability to create communications with in-the-moment relevancy for multi-channel customers, anomaly detection and transaction analysis to prevent fraud, operational intelligence and real-time use of streaming data from connected devices that comprise the internet of things.

“Cloud computing has witnessed massive growth over the years and is still gaining clout. In our conversations with prospects, customers and partners, it is clear to us that enterprises are relying more and more on cloud services to handle their data workloads,” said Punit Shah, the Lead Solutions Architect for StreamAnalytix at Impetus Technologies. “In response to this shift, StreamAnalytix has been cloud ready for a while, with deployment options available for both AWS and Azure. Now, the official launch on AWS marketplace further cements our focus on providing a robust cloud ecosystem for StreamAnalytix enterprise users.”


IoT Innovator Newsletter

Get the latest updates and industry news in your inbox! Enter your email address and name below to be the first to know.