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 In-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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StreamAnalytix Lite

StreamAnalytix Lite makes Spark easy and expands the base of users that can build Spark based applications. It off¬ers an easy-to-use visual Integrated Development Environment (IDE) to build, deploy and manage Spark based enterprise grade applications.

Operationalize Machine Learning at Scale with StreamAnalytix

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