What is StreamAnalytix?

StreamAnalytix is an enterprise grade visual platform for all your streaming and batch data processing and analytics needs.

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.

Build and operationalize big data applications five to ten times 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.

With support for multiple big data engines and built-in extensibility StreamAnalytix gives you full flexibility and control to work with the technology stack of your choice.

StreamAnalytix Overview

Rapidly build and operationalize stream processing and machine learning applications

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?

Unified Stream and Batch

Support all use cases; real-time, near real-time or batch.

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

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

Visual Data 360

A one-stop-shop for your end-to-end data processing journey:
data ingestion, data quality, data blending, data transformation, analytics, machine learning, action triggers, storage and visualization.

Open Source Flexibility

Ensure future readiness, avoid vendor lock-in.
Work with the power and flexibility of best-of-breed open source technologies integrated into a high-performance, scalable, and reliable enterprise-grade platform.

Strong Data Science

Operationalize machine learning at scale, on real-time data.

Use a comprehensive set of advanced analytics and machine learning operators, like Spark MLlib, Spark ML, PMML, H2O, Tensorflow and more.

Enables model training and scoring, across real-time and batch workflows.

Use features like A/B testing and model swap with champion challenger.

Click + Code

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

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

Multi-Engine Support

A single, consistent user experience for application development, over multiple big data engines:
Apache Spark, Apache Storm, Tensorflow, and Apache Flink.

Build and interconnect application sub-systems that each leverage the best-suited engine.

Technology Agnostic and

Keep full control and the flexibility to add new functionality and interfaces
as the technology ecosystem evolves.

Strong Ecosystem

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.

On-premise, Cloud
or Hybrid

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


Use pre-built templates
for frequently used application patterns and customize them to your needs.
Easily access support and tutorials at every step.

Start your free trial

of StreamAnalytix



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StreamAnalytix Platform Overview

StreamAnalytix™ enables enterprises to analyse and respond to events in real-time at Big Data scale using Stream processing and Machine Learning….

Spark + AI Summit 2018


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blog May 31, 2018

StreamAnalytix to demonstrate Apache Spark-based real-time streaming analytics and machine learning capabilities at Spark + AI Summit, San Francisco

We are happy to announce that StreamAnalytix is a gold sponsor and exhibitor at Spark + AI Summit, to be…