What is StreamAnalytix?

StreamAnalytix is an enterprise grade visual platform for all your batch and stream 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 Batch and Stream Processing

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

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.

Visual Data 360

A one-stop-shop for your end-to-end big 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.

Data Science Platform

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 Extensible

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

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.

On-premise, Cloud, or Hybrid

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

Self-service

Use pre-built templatesfor frequently used application patterns and customize them to your needs.

Easily access support and tutorials at every step.

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Resources

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StreamAnalytix Platform Overview

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