True stream analytics platforms ingest, integrate and analyze unstructured, structured, local, distributed, in-motion and at-rest data continuously, concurrently, and at rates of millions of records per second per core. Of all, Guavus SQLstream is the only that’s truly easy to use.
At the heart of Guavus SQLstream is a rich and flexible set of operators to efficiently process and analyze incoming data streams.
SQLstream’s approach to streaming:
Guavus SQLstream can process over 1 Million 16-byte records/sec per CPU core while scaling linearly to over 16 cores on commodity hardware.
StreamLab opens stream processing to BIs and data scientists, who can interactively explore machine data streams and building real-time streaming apps without having to write any code. Features:
Guavus SQLstream works with any data source, format or destination, concurrently, continuously, and in real-time.
By redundantly computing the results of all stream operations on multiple commodity nodes, Guavus SQLstream achieves arbitrary “x9”s of availability in real-world apps without compromising performance or resorting to exotic and costly hardware.
case study: infoarmor
InfoArmor, a data security company, employed Guavus SQLstream to power its real-time security intelligence platform servicing over 600 banks and financial institutions, thus improving its services and increasing its customer base capacity from 600k to over 10M. The SQLstream analytics solution runs continuous analytics on all data streams and automatically deploys user-authorization revisions and real-time alerts when network or user security is at risk.
Guavus SQLstream’s mission is to make real-time stream analytics easy to use and own with a one-stop-shop solution that performs the best, has the widest footprint, never turns off, and can be developed and customized by data scientists and engineers alike.
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