StreamAnalytix brings data engineers, data scientists, and business analysts together. It enables self-service data processing, analytics and machine learning, in a unified collaborative platform for the front lines of your business.

 

A Visual Platform for Data 360

Build and operationalize applications 10x faster using a visual drag-and-drop interface, an exhaustive set of pre-built operators, full application lifecycle support, and one-click options for on-premise and cloud deployments.

StreamAnalytix Overview

Ingest, blend, and process high velocity big data streams as they arrive, run machine learning models, visualize results on real-time dashboards, and train and refresh models in real-time or in batch mode

Developer DevOps specialist Data Scientist Business Analyst Real-time Data Ingest Data Preparation Predictive Analytics & Machine Learning Deep Learning Data Sinks Alerts & Actions Real-time Dashboards Static Data Ingest BI Tools Enterprise Applications Administration & Security Application Lifecycle Statistical Analytics & Custom Business Logic Open Source Big Data Processing Engines

Why StreamAnalytix?

Cloud, Hybrid, and On-premise

Build on-premise or cloud applications that connect to infrastructure components
and services no matter where they are.

Unified Batch and Stream Processing

Ingest and blend data at scale from any batch or streaming data source.

Use models trained and refreshed in batch workflows to make predictions on real-time data pipelines.

End-to-end Data Processing and Analytics

Data ingestion, ETL, analytics, machine learning, action triggers, storage and visualization

Built on Apache Spark

Provides a visual IDE for 10x faster Spark application development vs. hand coding.

Offers multi-engine support across: Apache Spark, Apache Storm, Tensorflow, and Apache Flink.

Self-Service

Empowers a broad set of users to explore complex data at scale, and have greater control over the end analytic output

Click + Code and Reuse

Use pre-integrated drag-and-drop operators in a visual UI.

Introduce or reuse custom logic where needed, in the language of your choice (Java, Scala, and Python).

Supports Complete Data Science Lifecycle

Explore data with a Notebook IDE.

Train and score models across real-time or batch workflows using a visual IDE.

Strong Ecosystem Integration

Compatible and integrated with leading big data technologies and platforms

Hadoop distributions: MapR, Hortonworks, and Cloudera.

Cloud platforms: Amazon Web Services, Microsoft Azure

Key 3rd party partnerships: Attunity, DataStax, Couchbase, ElasticSearch, Kyvos Insights, Marketo, SalesForce, and more.

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Resources

data sheets

Leveraging continuous integration, delivery, and deployment(CI/CD) in StreamAnalytix

Continuous Integration and Delivery (CI/CD) is a set of automated SDLC practices and methods that enable frequent and error-free releases…

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blog Jul 09, 2020

StreamAnalytix Cloud – Your next-generation tool for self-service ETL and machine learning

Impetus’ StreamAnalytix Cloud is fast transforming the industry’s extract, transform, load (ETL) landscape. Enterprises can now effortlessly build ETL flows on the cloud, leveraging an intuitive drag-and-drop interface. They can move, cleanse, and transform data in the cloud from any source within minutes to accelerate Spark application development like never before. StreamAnalytix Cloud is live on AWS Marketplace and will soon be available on Azure and Google Cloud.

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