The store-before-query analytics and conventional ETL models are irrelevant in a world where streaming analytics can empower businesses to take the next right action, continuously and real time.
CA, San Francisco (PRWEB) August 11, 2016
SQLstream, the leading streaming analytics platform provider, today announced that Amazon Web Services (AWS) has licensed and implemented a subset of core technology from SQLstream Blaze, its streaming analytics platform. This technology powers the Amazon Kinesis Analytics service announced today by AWS, and enables Amazon Kinesis Analytics developers to get actionable insights from streaming data continuously and in real time, using standard SQL.
SQLstream is also announcing the SQLstream Blaze Adapter for Amazon Kinesis Analytics. The SQLstream Blaze Adapter enables businesses to securely and cost-effectively ingest, analyze, and manage streaming data on and between cloud and on-premises environments.
IoT applications, mobile devices, wearables, industrial sensors, as well as many software applications and services can generate staggering amounts of streaming data – sometimes TBs per hour – that need to be ingested, analyzed, and managed as the data arrive, to enable valuable business actions continuously and in real time. The combination of Amazon Kinesis Analytics and SQLstream Blaze offers the best of on-premises and cloud advantages.
With a streaming analytics solution that includes SQLstream Blaze and Amazon Kinesis Analytics, customers can:
- Easily ingest streaming data within cloud and on-premises environments: Discovery and automatic ingest and transform any data format – structured or unstructured, live or historical, in motion or at rest – from or to any data format, interfacing with a wide array of sources and destinations including Amazon Kinesis and Firehose, Hadoop, data warehouses, message buses (including Kafka), files, and devices.
- Easily ingest all data into and out of AWS: Streaming ingestion allows data to be moved continuously and in real time from data sources, to the cloud, and from the cloud through a high performance bi-directional SQLstream Blaze Kinesis Adapter.
- Painlessly operationalize insights continuously and in real time: Analysis of high-volume, high-velocity data, turning it into actionable information with millisecond latency using SQLstream Blaze technology licensed by AWS. Live data streams are integrated and analyzed with historical data for accurate business context, record by record, eliminating the risk of incomplete analysis for time sensitive decisions, due to batch or micro-batch processing.
- Deploy real-time analytics at the edge for a far lower cost: Developing streaming applications and deploying them for optimal performance near data sources at the edge, on premises, or in the cloud. Declarative SQL allows automatic optimization and parallelization, dramatically reducing runtime footprint and hardware requirements. Streaming analytics enables data to be analyzed and acted on as the data arrive, without needing to store, eliminating unnecessary security risks and storage costs.
- Centralize streaming data visibility and security at global scale: Global view of data flowing through deployments using telemetry provided by Blaze. Data can be managed and marshalled for storage or analyzed without storing, for optimal value and security.
- Use existing apps, databases, data warehouses, and skillsets: Using data from existing sources and writing standard SQL queries on streaming data, without having to learn any new programming skills. In addition, the SQLstream development environment, StreamLab, enables data analysts and SQL, Java, Python, and Scala developers to build streaming applications in minutes.
- Zero downtime: Maintain continuous business operations while changing streaming application logic or queries, on-the-fly, while data is in motion.
- Automate accurate, contextual actions: Operationalizing actions with applications that deliver triggers and alerts based on real-time, record-by-record contextual analysis of live and historical data, including time-series and spatial operators.
"The store-before-query analytics and conventional ETL models are irrelevant in a world where streaming analytics can empower businesses to take the next right action, continuously and real time,” said Damian Black, CEO of SQLstream. “The combination of Amazon Kinesis Analytics and SQLstream Blaze makes it easier than ever for businesses to securely and cost-effectively ingest, analyze, and manage streaming data on and between public cloud, private cloud, and on premises.”
SQLstream empowers people, services, and machines to take the next right action, continuously and in real time. SQLstream has designed its streaming analytics platform to enable anyone to create real-time applications from raw data in minutes, that deliver streaming data ingestion, streaming analytics, and live actions. SQLstream offers the only solution enabling businesses to continuously respond to changing conditions, every moment. SQLstream is based in San Francisco, California. Download SQLstream Blaze for a live experience at http://sqlstream.com/download/.
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