SAS Event Stream Processing

Seize opportunities and spot red flags hidden in torrents of fast-moving data flowing through your business using event streaming analytics.

Use machine learning to gain insights for taking the right action

Streaming data from operations, transactions, sensors and IoT devices is valuable – when it's well-understood. Event stream processing from SAS includes streaming data quality and analytics – and a vast array of SAS and open source machine learning and high-frequency analytics for connecting, deciphering, cleansing and understanding streaming data – in one solution. No matter how fast your data moves, how much data you have, or how many data sources you’re pulling from, it’s all under your control via a single, intuitive interface. You can define patterns and address scenarios from all aspects of your business, giving you the power to stay agile and tackle issues as they arise.

Make sound big data decisions

Filter, normalize, categorize, aggregate, standardize and cleanse big data before you store it – saving significant staff and computing resources from having to clean up data lakes. Prebuilt data quality routines and text processing execution are applied to data in motion so big data is filtered and ready for consumption.

Scale economically from edge to cloud for growing data volumes

Faster, better, more powerful stream processing from edge to enterprise for high-volume throughput (millions of events per second) means low-latency response times running in distributed, in-memory grid processing commodity hardware environments. Analyze structured and unstructured data sources – including video, text, and image classification and identification – using advanced analytics with embedded AI and machine learning capabilities. In addition, SAS Event Stream Manager integrates SAS Event Stream Processing studio and server components, simplifying and automating the deployment of SAS Event Stream Processing projects and analytics for rapid decision making – with no disruption to service.

Key features

Uncover insights at the edge and make real-time, intelligent decisions in the cloud using machine learning and streaming analytics.

Built for speed

Process large volumes of data. Handle millions of events per second with low latency, while supporting GPU acceleration.

Seamless integration

Consume today’s leading data sources in the cloud or at the edge, enabled by a comprehensive catalog of diverse prebuilt connectors and adapters.

Intuitive design environment

Easily build and test your models in a user-friendly, low-code environment to validate your project. Manage versions and promote projects to production with a streamlined workflow.

Instant insights, faster response

Empower your decisions with real-time alerts, tailored notifications and proactive updates, ensuring you're always one step ahead.

Analytics anywhere

Enhance your data streams with advanced analytical techniques and machine learning, available from the edge to the cloud.

Unified management & monitoring

Optimize your projects with status reporting, direct access to log files, built-in auditing, utilization tracking, real-time performance monitoring and intelligent resource management.

Native cloud support

Compatible with cloud technologies, utilizing Docker and Kubernetes for large-scale, elastic, distributed services.

Streaming fault tolerance

SAS patented 1+N-Way Failover system offers uninterrupted, secure and reliable service without data storage needs.

Simplified computer vision

Perform inference on video and still image data using streaming analytics for preprocessing, object detection and classification, supported by SAS and third-party machine learning frameworks.

Enablement & support

Access SAS code examples, libraries and tools on Git, and connect with other users in our SAS communities for collaboration and support.

Custom windows

Design new windows, reuse them across projects and share them with others to boost efficiency.