Kyligence Launches Intelligent Data Cloud for Interactive Analytics at Massive Concurrency and Scale

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

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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 can routinely deliver sub-second query response times against datasets of hundreds of terabytes to petabytes.

“I’m very excited about our partnership with Kyligence,” said Brian Parone, CTO, risk technology, UBS. “Kyligence Cloud is a foundational technology at the heart of our centralized reporting platform built upon our Azure-based data lake. Now, for the first time, we are able to combine our data from Risk, Finance, and Treasury creating a unified reporting layer.”

“As the race for unified analytics heats up, Kyligence offers a solution that overcomes the challenges of querying data in both data lakes and data warehouses located both in the cloud and on premises,” said John Santaferraro, research director for analytics, EMA. “While this is being attempted by other vendors, Kyligence also solves the need for high performance, real-time analytics required by digital business. Looking forward, EMA expects Kyligence to further advance its use of artificial intelligence in the platform to automate even more aspects of unified analytics.”

Kyligence Cloud 4 drastically 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.

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Through the use of machine learning, Kyligence Cloud’s AI-augmented engine automatically identifies the most frequently accessed datasets 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 significantly reduces operating and maintenance costs. In addition, it dramatically increases the number of concurrent users conducting data analytics on these platforms, which is the best option to deliver 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 datasets they curate.”

Key features of Kyligence Cloud 4 include:

• Unified Semantic Service – Abstracted from different data sources on cloud and performs as a centralized data service for all kinds of analytics with one single data view. It does not require the need to move all data from one source to another. It’s easy to architect a SQL service on top of Cloud Storage like S3 directly, and with its complex calculation logic and security, ACL settings are no longer tied to specific BI tools and platforms. Instead, they are now available to all 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 drastically reduce the time to prepare data services for data science, machine learning, and SaaS analytics workloads.
• Cloud Native Architecture based on Open Source – Designed and built for today’s cloud, Kyligence Cloud is powered by Apache Kylin with added machine intelligence, support for all popular BI tools (Excel, Microstrategy, Power BI, Tableau, Qlik) and back end data platforms (Snowflake, AWS S3, Azure Data Lake Storage, 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 drastically reduces the load on back end systems like Snowflake and Synapse, and lowers cloud infrastructure costs.
• Smart Pushdown™ – The benefit of smart routing and pushdown is to enable the best 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.

“Contrary to popular belief, OLAP isn’t dead. It has not been killed by big data,” said Mike Leone, senior analyst, ESG. “There are many companies – along with millions of users, cubes, and experts – that continue to leverage OLAP, and have turned to Apache Kylin and Kyligence Cloud for better enablement. The latest release, Kyligence Cloud 4, redefines what OLAP means for those embracing cloud analytics, reinvigorating life back into lagging BI implementations.”

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