Create fully functional ingestion flows within minutes
A Spark-based visual self-service data flow and analytics platform
Build applications 10x faster | Pre-built operators | Full lifecycle support | Cloud and on-premise
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Build, operationalize, and manage machine learning models at scale
Move, cleanse, and transform your data in the cloud from any source within minutes
Enable your data-flow journey with self-service data processing, machine learning, and DataOps
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
Why StreamAnalytix?
Multi and hybrid cloud support
Build your applications and pipelines and host them on any cloud provider of your choice or on a hybrid environment
Unified batch and stream processing
Ingest and blend data at scale from any batch or streaming data source. Unified batch and stream processing
End-to-end data processing and analytics
Supports data ingestion, data preparation and processing, analytics, data science and machine learning, action triggers, data visualization, and data storage
Multi-engine support
Leverage Apache Spark and other compute engines including Apache Storm, Apache Flink, TensorFlow, and Oozie for 10x faster application development vs. hand-coding
Self-service
Take advantage of 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 an exhaustive set of pre-integrated drag-and-drop operators in an intuitive visual interface, or introduce custom logic in the language of your choice (Java, Scala, or Python)
Application data flow lifecycle management
Build applications with end-to-end support for the entire application delivery lifecycle – design,
Open source flexibility
Take advantage of the best-of-breed open source technologies integrated into a high-performance, build, test, debug, deploy, monitor, and manage scalable, and reliable enterprise-grade platform
Workflow orchestration
Integrate multiple pipelines to work in sync and automate the execution of multiple inter-related tasks
Extensibility
Keep full control and flexibility to add new functionality and interfaces as the technology ecosystem evolves
Resources
blog Nov 24, 2022
ETL vs ELT: Which data integration practice is right for you
ETL and ELT are common data integration processes that are extensively used in data science and business intelligence. While leading…