GigaSpaces announces InsightEdge data lake accelerator, AnalyticsXtreme, for faster, smarter real-time analytics


GigaSpaces, the provider of InsightEdge, the in-memory real-time analytics platform for instant insights to action, announced AnalyticsXtreme, accelerating access to data lakes and data warehouses by up to 100X  and simplifying development and deployment of applications for faster time to market on-premise and in the cloud. 

AnalyticsXtreme accelerates applications, in which real-time analytics, machine learning and deep learning are used for real time insights such as predictive maintenance, live risk analysis, fraud detection, location based advertising, dynamic pricing and more.

AnalyticsXtreme powers interactive queries and machine learning models to run simultaneously on both real-time mutable streaming data and on historical data that is stored on data lakes based on Hadoop, Amazon S3 or Azure Blob Storage, as well as data warehouses, such as Snowflake, without requiring a separate data load procedure or data duplication.  Moving from on premise to the cloud, or changing technology stacks for example from Cloudera to Amazon S3 is seamless to machine learning applications; increasing flexibility while reducing development and maintenance costs. This level of integration is achieved automatically without requiring any changes in the data structures or logic in the machine learning apps; solving the complexities of big data architectures such as Lambda.

Combined with GigaSpaces MemoryXtend module, AnalyticsXtreme allows enterprises to leverage business-driven policy to automatically auto-tier hot and warm data between RAM, Persistent Memory, Storage Class Memory and SSD, as well as automatically move data for cold storage, and archiving to data lakes and data warehouses. 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. Access to data is accelerated by up to 100X for faster, smarter insights that are instantly actionable.

The solution also provides a single logical view of data that spans across real-time and historical data platforms, including SQL, Spark dataset/dataframe as well as BI tools, like Tableau and Looker.

“Today our customers want to not only accelerate batch analytics, but also require event driven analytics and machine learning in real-time for smarter insights that can be acted upon instantly,” said Yoav Einav, VP Product at GigaSpaces.  “AnalyticsXtreme further simplifies enterprise big data architecture in the cloud and on-premise with the fastest software platform that can seamlessly plug and play on existing infrastructure such as Hadoop and Amazon S3. It reduces long ETL processes, eliminates unnecessary data duplication and avoids data ingestion bottlenecks from various data sources.”

AnalyticsXtreme benefits include:

  • Faster, smarter  analytics  
    • Real-time access to and analytics on frequently used mutable data and historical data with out-of-the-box ETL
    • Acceleration of batch analytics by orders of magnitude, from days to hours or hours to minutes
  • Faster time-to-market
    • Agile application development  leveraging unified API access to reliable, strongly  consistent data across real-time and historical platforms
    • Interactive SQL queries, Machine Learning with Spark dataset/dataframes and JDBC driver for live connections over BI tools, like Tableau and Looker on a unified real-time and historical view
  • Greater simplicity
    • 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

AnalyticsXtreme is available as part of the InsightEdge in-memory computing platform which provides high-throughput ACID transactional processing, stream processing, and co-location of applications and analytics to enable organizations to act on time-sensitive data as it is born at millisecond performance.

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