AnalyticsXtreme, offered as part of the InsightEdge platform, powers insight-driven organizations to address time-sensitive business decisions with smarter and faster analytics. AnalyticsXtreme accelerates access to data lakes and data warehouses by 100X and simplifies development and deployment of applications for faster time to market on-premise and in the cloud. Applications can leverage real-time machine learning and deep learning models on both hot mutable data combined with historical data which is stored in data lakes and data warehouses from a unified API. This provides a single logical view of data that is spanned across real-time and historical data platforms, including SQL, Spark dataset/dataframe as well as BI tools, like Tableau and Looker.
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AnalyticsXtreme in-memory performance powers:
- Real-time machine learning and advanced analytical models on both hot, mutable data and historical data for faster and smarter insights. You move seamlessly from raw data to
real time - Acceleration of batch analytics from days to hours or hours to minutes
Unified API access accelerates development and deployment while ensuring data consistency:
- Agile application development leveraging unified access to reliable, strongly consistent data across real-time and historical platforms
- Interactive SQL queries, Machine Learning with Spark dataset/
dataframes
AnalyticsXtreme simplifies the complexities of the Lambda architecture for:
- Simpler operations and data governance – automatic lifecycle policy handles the underlying data movement simplifying security and data management
- Seamless multi-region and multi-cloud replication for data lakes and data warehouses
Intelligent tiered storage capabilities deliver business-driven policies to automatically auto-tier hot and warm data between RAM, Persistent Memory, Storage Class Memory
By utilizing these advanced mechanisms for intelligent tiering, data is efficiently stored in the right storage layer based on performance, while optimizing infrastructure costs across the entire solution and data lifecycle.
