Contextualize Customer Experiences

Deliver personalized interactions that are relevant in the moment

Gain Real-time Operational Intelligence

Dramatically increase operational efficiency across your enterprise

Sense and Respond to IoT Data

Process, analyze and gain insights from thousands of IoT devices in real-time

Process Reality as It Happens

With StreamAnalytix

Build and deploy batch and stream processing use cases rapidly with best-of-breed open-source technologies,
both on-premise and in the cloud

Unify Batch and Streaming
Data Analytics

Ingest and blend big data flows into your data lake; from any batch or streaming data source

Leverage Multi-engine

Get a consistent user experience across Apache SparkTM, Apache StormTM, Apache FlinkTM, TensorFlowTM and OozieTM

Apply Machine Learning
on Real-time Data

Easily build models using a comprehensive set of machine learning operators. Train and score models on real-time data or in batch mode

Open Source Enabled Enterprise-grade Platform

Ensure future readiness and avoid vendor lock-in with open-source flexibility, combined with a scalable and secure platform

Build Big Data Applications Visually

Data 360

An end-to-end big data processing platform− data ingestion, data analytics, machine learning, action triggers, and data visualization

Intuitive UI

Offers the ease and power of a visual IDE over a complex mix of big data analytics technologies

Click + Code

Use pre-integrated drag-and-drop operators or introduce hand-written custom logic

Optimized Solutions Across Use Cases

Credit Card Fraud Detection in Real-time

A large US bank predicts and curbs credit card fraud through real-time analytics using StreamAnalytix.

  • Cluster models identify fraudulent transactions in real-time, based on historical data
  • Classification of fraudulent transactions is continuously updated in real-time
  • Transactions are further classified by value and volume (low to high)
  • Custom alerts are created for various retail merchants and zip codes
  • Allows summary report for any interval
  • Enables persisting of identified patterns for future analysis and offline reporting
  • New models can be implemented in a weeks’ time

Connected Car Solution

StreamAnalytix enabled a large US based auto insurance provider to build an end-to-end real-time big data analytics application for driver profiling and risk assessment. The application enabled a new usage based insurance offering.

  • Enabled an individual risk assessment model based on real-time analytics of incoming streaming data around; driving behavior, vehicle usage and performance data, and third-party data like weather and driving conditions
  • The driver profiling and vehicle risk assessment enabled a highly personalized pricing and discounting options
  • Additionally, enabled remote vehicle diagnostics and predictive maintenance services

Anomaly Detection in Real-time

Identify outliers through real-time analytics of transactional data, log data, customer behavior, and other historical data. Gain actionable insights in a wide variety of application domains such as: fraud detection, network traffic management, predictive healthcare, energy monitoring and many more.

A few examples include:

  • Analyze log data to detect network anomalies like suspicious behavior or patterns from malicious users/applications or faulty devices
  • Predict and prevent loss of a customer by identifying behavior patterns leading to a possible churn
  • Detect fraudulent patterns in massive stock market streaming data sets by using unsupervised learning methods, to identify anomalies such as market manipulation and price rigging

Call Centre Analytics

A tier 1 contact center deployed a new real-time call center analytics and infrastructure monitoring system with StreamAnalytix. It allows unified real-time analytics of events that are scattered across different media networks and geographies

  • Enables tracing of the complete call flow, and raising service alerts based on real-time data analytics
  • Allows call stitching in real-time (view, sort, filter and zoom into a call), and identifying top 10 most dominant call paths
  • Real-time sentiment analysis of multi-lingual text data, including: alerts on emails and conversations
  • Predicts future pricing models and requirements

Apache Spark - Visualized. Simplified.

With StreamAnalytix Lite

StreamAnalytix Lite is a free and compact, Apache Spark only, desktop version of the StreamAnalytix Enterprise Edition

Get a lightweight tool for your
desktop or laptop

Use an intuitive drag-and-drop interface to fast-track your Apache Spark application development

Find all your Apache Spark connectors pre-built in one unified development tool

A powerful visual IDE to build, test and run Apache Spark applications on your desktop− for free


4 Reasons to Choose Apache Spark for All Your Data Processing Needs

Find Out

Top Companies are Benefiting from StreamAnalytix

This is how Fortune 500 companies are creating value

10x Faster

Build Big Data applications
5x to 10x faster

Pharma major builds &
deploys 2 critical Spark
pipelines in 2 days >

4x Performance

4x boost in performance
at the same cost

Major bank onboards
5x more application traffic
on existing hardware >

3x Gain in

Have your existing team
work seamlessly with the changing technology landscape

Telco giant increases
team productivity by
a dramatic 70% >

1 Mn+ Events
Per Second

Process millions of events per second - both on-prem and in the cloud

Major auto insurer offers
usage-based insurance
based on telematics data >

Recognized By


One of 13 Most Significant Stream Analytics Providers

The Forrester Wave™: Streaming Analytics, Q3'17

Read More

Aragon Research

One of 4 Hot Vendors in the Stream Analytics Space in 2017

Hot Vendors in Streaming Analytics, 2017

Read More


One of the Key Event Stream Processing Platforms

Market Guide for Event Stream Processing, 2017

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Best Big Data Analytics Product or Technology: Real-time Analytics

Datanami Editors' Choice Award

Read More

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of StreamAnalytix



StreamAnalytix Lite NOW

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