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RESEARCH & RESOURCES

Kyligence Releases Data Cloud Platform for Interactive Analytics

AI-augmented Kyligence Cloud 4 offers a cloud-native distributed OLAP analytics solution to deliver sub-second query response time against petabytes of data.

Note: TDWI’s editors carefully choose vendor-issued press releases about new or upgraded products and services. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the vendor's statements.

Kyligence, originator of Apache Kylin and developer of the AI-augmented analytics Kyligence Cloud platform, released Kyligence Cloud 4, its new cloud-native distributed big data analytics platform. 

Available on Microsoft Azure and Amazon AWS, Kyligence Cloud 4 leverages cloud-native concepts such as the separate scaling of compute and storage to enable fast, scalable and highly concurrent analytics against cloud data warehouses and data lakes. It combines high performance and high concurrency OLAP, a cloud-native architecture, and auto-optimization using machine learning algorithms to simplify and automate cloud analytics. Kyligence Cloud 4 is designed to deliver sub-second query response times against datasets of hundreds of terabytes to petabytes.

Kyligence Cloud 4 reduces cloud analytics costs by offloading processing from cloud data warehouses and data lakes by employing distributed aggregate indexes -- a cloud-native successor to OLAP cubes. Kyligence Cloud also provides intelligent query routing and Smart Pushdown that ensures queries of all kinds are delivered with optimal performance. With its Unified Semantic Service, Kyligence Cloud offers a consolidated analytical view across enterprise data sources to build a single expression of truth for business users. 

Through the use of machine learning, Kyligence Cloud’s AI-augmented engine automatically identifies the most frequently accessed data sets from SQL query history, analyst usage patterns, data profiles, and runtime metrics and uses that intelligence to efficiently rationalize analytical models. Kyligence Cloud has an intuitive administrative user experience that reduces operating and maintenance costs. In addition, it increases the number of concurrent users conducting data analytics on these platforms, which is a good option for delivering data-as-a-service to machine learning and SaaS analytics applications.

“When a significant proportion of your IT budget is allocated to cloud services, significant performance gains translate to pure savings in the cloud,” said Li Kang, vice president of North America, Kyligence. “Kyligence Cloud functions as a high-performance data service that delivers unified semantics and supports SQL, MDX, and REST interfaces. Our mission is to follow a cloud-native approach to enable data engineers and SQL experts to build high performance into the data sets they curate.”

Key features of Kyligence Cloud 4 include:

  • Unified semantic service. Abstracted from different data sources on the cloud, it operates as a centralized data service for all kinds of analytics with one single data view. It does not require transfer of all data from one source to another. It facilitates architecting a SQL service on top of cloud storage such as S3 directly, and with its complex calculation logic and security, ACL settings are no longer tied to specific BI tools and platforms. They are available to business users no matter what BI tools they choose.

  • AI-Augmented engine. Machine learning algorithms are used to continually improve performance by auto indexing based on query history and user behavior. It also provides automation of data modeling that can reduce the time to prepare data services for data science, machine learning, and SaaS analytics workloads.

  • Cloud-native architecture based on open source. Kyligence Cloud is powered by Apache Kylin with added machine intelligence, support for popular BI tools (such as Excel, MicroStrategy, Power BI, Tableau, and Qlik) and back-end data platforms (including Snowflake, AWS S3, Azure Data Lake Storage, and Azure Blob Storage.)

  • Intelligent distributed OLAP. Using precomputed aggregate indexes, smart indexes, and smart pushdown, Kyligence Cloud 4 delivers sub-second query response times on petabyte-scale datasets. This reduces the load on back end systems including Snowflake and Synapse.

  • Smart pushdown. Smart routing and pushdown enable a strategy to maximize sub-second response times without sacrificing the ability to run ad hoc or detailed queries. This also removes the need to move data for data discovery and exploration.

 For details, visit https://kyligence.io/.

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