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GigaSpaces InsightEdge
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GigaSpaces InsightEdge
By GigaSpaces Technologies Inc
Certified enterprise ready
Runs services and machine learning models in production, at extreme speed and scale, across on-premise, cloud and hybrid.
Software version
15.0
Runs on
OpenShift 4.6 - 4.9
Delivery method
Operator
Products purchased on Red Hat Marketplace are supported by the provider. Beyond documentation and developer communities, specialists and product maintainers may be available to address your concerns.
FAQs
The InsightEdge Platform unifies Transactional, Analytical and ML processing in a single platform powering real-time decision making:
- Extreme speed and scale
- Ingesting, processing and storing ANY Data model
- Seamless handling of peaks
You can create a distributed data fabric to store data across RAM, SSD, and Persistent Memory transparently, to accelerate access to data, maximize processing and run real-time advanced analytics and AI on terabytes of data.
With the InsightEdge MemoryXtend multi-tiered storage solution, you can match your preferences for data prioritization and access patterns in any granularity (per application, table or field).
You can control where your hot, warm and cold data resides to balance between performance and cost. This ensures that your most important data resides in the fastest data storage tier to optimize the business results of each application while lowering total cost of ownership (TCO).
For business continuity, MemoryXtend also supports near-real-time parallel initial load of huge datasets.You can leverage the InsightEdge JDBC driver with existing visualization tools, to accelerate reporting by 30X and visualize operational data as it's born.
The Spark framework is an integral part of the InsightEdge platform. The tight integration:
Increases Speed: InsightEdge minimizes data movement to practically zero, since the actual Spark models run in the same memory space as the actual data residing on the distributed system. Advanced indexing also provides 30x faster read performance, and optimization using filtering and aggregations.
Increases Resiliency: Spark storage persistency is based on a file system (HDFS) or a cloud blob storage (Amazon S3 & Azure ADLS), which means every time you restart a cluster or a spark executor, the data is lost and must be reloaded. With InsightEdge high availability, there is no need to reload the data and recovery is instantaneous.Optimizes TCO: Spark is usually run on immutable data (append-only) which are copies/snapshots; significantly increasing the storage footprint. InsightEdge lets you run analytics and ML on mutable data (objects, documents, key-value)
You can replicate your data for mission-critical applications spanned across multi-geographical sites at sub-second latency to ensure business continuity across sites, zones and regions. The replication is done efficiently in order to optimize the bandwidth and strain on your network as well as to ensure that the data is immediately available locally for any application.
Running your business logic close to the data source across all sites optimizes availability and speed for best performance.AnalyticsXtreme, offered as part of the InsightEdge platform 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.
- Acceleration
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 insights without cumbersome implementation and maintenance of ETL processes
- Acceleration of batch analytics from days to hours or hours to minutes
- Faster time-to-market
A 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 and JDBC driver for live connections over BI tools, like Tableau and Looker on a unified real-time and historical view
- Greater Simplicity
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
- Optimized TCO
Intelligent tiered storage capabilities deliver business-driven policies 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.
- Acceleration
Yes. GigaSpaces applications provide continuous high-availability even when the infrastructure processes or entire (physical/virtual) machines fail. This capability is provided out of the box.