SQLstream Releases SQLstream Blaze 5.2 with Machine Learning Support at Kafka Summit in San Francisco
SQLstream Blaze, the technology bringing Streaming Analytics and data wrangling to Apache Kafka™, now offers real-time declarative predictions with continuous machine learning
San Francisco | August 22nd, 2017 – SQLstream, the leading stream analytics and data wrangling technology provider, today announced the release of SQLstream Blaze 5.2 at the Kafka Summit in San Francisco. SQLstream Blaze is the only technology bringing SQL-based streaming analytics and real-time data wrangling capabilities to existing Apache Kafka™ implementations. The new 5.2 version supports Apache SystemML, enabling Kafka users to add real-time declarative predictions with continuous machine learning.
Held at the San Francisco Hilton Union Square on August 28th, Kafka Summit is the premier streaming systems event for data engineers and developers, and brings the Apache Kafka™ community together to share best practices, write code and discuss the future of streaming technologies.
At the SQLstream booth, our team will show how analysts and developers can go from raw data to complete apps in minutes using SQLstream Blaze 5.2, automatically discovering data formats, parsing and making intelligent analytics recommendations while integrating all sources and formats of data in real time.
SQLstream Blaze 5.2 is a complete, distributed, SQL standards-compliant streaming data management system, capable of:
- High-availability, fault-tolerant operations for applications and services that can be run and updated continuously with the data still flowing.
- Intuitive interaction through real-time data wrangling that allows technical and non-technical users alike to go from raw data to deployed streaming applications in minutes.
- High-performance parsing and analytics of streaming data, both structured and unstructured, from all formats and at rates exceeding 1 million records per second per CPU core and in-server latency as low as 1 millisecond or less.
- Seamless integration with existing Big Data storage and enterprise systems.
- True real-time dashboarding and push-based visualization.
- Providing real-time predictive analytics with models that are continuously refined and reloaded without ever interrupting the data pipeline.
“Kafka is changing the Big Data landscape through scalable, affordable, low-latency streaming data distribution and dissemination. To it, SQLstream Blaze brings the industry-leading power of true SQL-standard streaming analytics, the amazing productivity of real-time data wrangling, the highest performance available of any streaming analytics platform, and now integrated machine learning capabilities” said Damian Black, CEO and co-Founder of SQLstream. “SQLstream Blaze disrupts real-time data processing in much the same way spreadsheets disrupted financial processing: with power, simplicity and unmatched elegance, plus performance that is off the charts.”
SQLstream delivers the only true standards-based SQL stream processing platform for real-time data wrangling, analytics, and action. Global enterprises use SQLstream Blaze to build streaming applications in minutes to keep operations running at optimal efficiency, protect systems from security threats, and support real-time customer engagement. With SQLstream Blaze, companies can go from raw data to actionable insights easily, continuously, and in real time, and compete effectively in the fast-changing business world. In 2016, AWS announced that Amazon Kinesis Analytics is based in part on technology components licensed from SQLstream. SQLstream is headquartered in San Francisco, California.