Logo
Sign in
Product Logo
Kyligence EnterpriseKyligence

Cloud-native OLAP platform for high-performance analytics on big data with intelligent query acceleration and semantic modeling.

Vendor

Vendor

Kyligence

Company Website

Company Website

US-only-Kyligence-Architecture-diagram.png
Product details

Kyligence Enterprise is a cloud-native OLAP (Online Analytical Processing) platform that delivers high-performance analytics on massive datasets. Built on Apache Kylin, it empowers organizations to unify data silos, accelerate query performance, and enable self-service analytics at scale. Designed for modern data architectures, Kyligence Enterprise supports hybrid and multi-cloud environments, offering a governed semantic layer and intelligent automation to simplify data operations and analytics.

Features

  • Cloud-Native Architecture: Designed for scalability and elasticity across hybrid and multi-cloud environments including AWS, Azure, and on-premises.
  • AI-Augmented OLAP Engine: Leverages machine learning to optimize query performance and automate data modeling.
  • Unified Semantic Layer: Provides a centralized, governed semantic model to ensure consistency and trust in business metrics across all analytics tools.
  • Smart Query Acceleration: Automatically identifies and accelerates frequently used queries, reducing latency and improving user experience.
  • Data Lake Integration: Seamlessly integrates with modern data lakes and warehouses such as Snowflake, Databricks, and Amazon Redshift.
  • Open APIs and BI Tool Compatibility: Supports integration with popular BI tools like Tableau, Power BI, Excel, and more.
  • Data Governance and Security: Offers fine-grained access control, auditing, and data lineage tracking to ensure compliance and data integrity.
  • High Concurrency and Performance: Supports thousands of concurrent users and sub-second query responses on petabyte-scale datasets.

Benefits

  • Accelerated Insights: Delivers lightning-fast query performance, enabling real-time decision-making.
  • Operational Efficiency: Reduces manual effort through AI-driven automation in data modeling and query optimization.
  • Consistent Analytics: Ensures all users access the same trusted metrics through a unified semantic layer.
  • Scalable and Flexible: Adapts to growing data volumes and user demands with support for hybrid and multi-cloud deployments.
  • Cost Optimization: Minimizes cloud compute costs through intelligent caching and workload optimization.
  • Empowered Business Users: Facilitates self-service analytics without compromising on governance or performance.
  • Enterprise-Grade Security: Built-in security and compliance features meet the needs of large organizations.