The Kinetica Streaming Data Warehouse Eliminates Legacy Analytics Latency with Simultaneous Streaming and Data Analysis

The cutting-edge platform draws on all data sources and applies integrated location, graph, and machine learning-powered analytics

Kinetica announced the latest release of The Kinetica Streaming Data Warehouse, a unified data analytics platform that delivers real-time analysis on incoming data streams, while incorporating all of an organization’s data and applying cutting-edge location intelligence and machine learning-powered predictive analytics. This release of The Kinetica Streaming Data Warehouse serves the most demanding enterprise requirements, including best-in-class security, resiliency, and ad hoc analytics on petabyte-scale data sets.

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Whereas the traditional data warehouse ingests and stores batch data for analysis, The Kinetica Streaming Data Warehouse ingests and stores a wide variety of data types and analyzes the data in real time as it is received. The key difference is that traditional data warehouses can perform analytics, but cannot run them in real time and are limited in the type of analytics they support. The Kinetica Streaming Data Warehouse is the only platform able to transform data in motion into immediate, usable insights, which require a streaming data warehouse.

“The Kinetica Streaming Data Warehouse serves organizations running analytics at scale that are blocked by unacceptably stale analytical results,” said Irina Farooq, CPO at Kinetica. “It is an ideal solution for organizations trying to both incorporate high-velocity streaming data and glean the full business context of all of their data, taking into account factors like location, time, and interrelationships. The platform is uniquely powerful because it analyzes and inferences streaming and historical data of many different types in real time at petabyte scale.”

The Kinetica Streaming Data Warehouse provides accelerated data science, is optimized for both on-premises and cloud deployment on the cloud of your choice, and leverages CPU and NVIDIA GPU data processing for low latency and maximum performance. Kinetica is built on a solid foundation of key partnerships, including NVIDIA-provided accelerated data analytics libraries and Oracle Cloud Infrastructure.

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The platform is fully ANSI SQL 92-compliant, and provides a comprehensive set of APIs to embed analytics in applications. It delivers results via any user interface the business requires, whether BI and reporting tools, apps, or out-of-the-box data visualization functionality. By taking an API-first approach to building data-driven applications, The Kinetica Streaming Data Warehouse can present data at any point of user interaction, giving businesses flexibility to use preferred tools, apps, and platforms across departments.

As a streaming data warehouse, Kinetica processes data in real time and unifies analysis of different data formats, such as relational, geospatial, graph, and time series data at scale. Kinetica’s latest release will deliver increased accuracy and detail to customers across industries.

Quotes:

“We have been working together with Kinetica over the past two years, delivering several use cases with massive datasets across our business of over 160 million customers. We leverage Kinetica for a security monitoring dashboard and business analytics use case with advanced geospatial visualization features and a highly extensible UDF framework,” said Tina Lusiana, VP of Business Intelligence and Analytics at Telkomsel. “We have been partnering closely with Kinetica, operating large Kinetica clusters towards excellent performance as part of our big data journey worth taking. In Kinetica 7.1, we aim to have significantly improved monitoring and alerting features, while also further exploring enhanced capabilities, including combined streaming and historical data analysis, location visualization, and machine learning-powered predictive analytics in a unified platform. These collaborations are part of our journey as a leading digital telecommunications company in Indonesia, to keep us moving forward in strengthening Indonesia’s digital lifestyle ecosystem.”

“Using Kinetica, our customers can visualize and analyze the latest energy data and analytics continuously at unmatched scale, guiding investment decisions,” said Mark Szygenda, CTO at Enverus. “Not only is the platform easier to configure, it’s also faster: we have already seen an impressive increase in data processing speeds, giving our customers a first-mover advantage over the competition.”

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“Combining real-time data streaming and analytics is a highly complex compute process that requires leading edge technology,” said Jim Scott, head of developer relations, data science at NVIDIA. “The NVIDIA accelerated computing platform efficiently enables The Kinetica Streaming Data Warehouse to best support customers across a broad range of industries to make informed, data-driven decisions in real time.”