LogIsland Reviews & Ratings

LogIsland

5.0 out of 5 stars

Ratings and Reviews 1 Rating

Total 5 out of 5 stars
ease 4 out of 5 stars
features 4 out of 5 stars
design 5 out of 5 stars
support 4 out of 5 stars

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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What is LogIsland?

The LogIsland platform is at the heart of Hurence's real-time analytics framework, allowing for the aggregation of factory events from the Industrial Internet of Things (IIoT) alongside data sourced from websites. Hurence claims that both manufacturing facilities and enterprises can be continuously monitored and analyzed through the extensive range of events they encounter, with each instance—such as a sales transaction, a robot completing a production task, or a product being shipped—considered an event. In essence, every action is classified as an event, and the LogIsland platform efficiently captures these occurrences, structuring them within a message bus designed to manage large data volumes. This infrastructure enables real-time analytical capabilities through a variety of plug-and-play analyzers, which range from simple tasks like counting and alert notifications to sophisticated artificial intelligence models that focus on predictive analytics and the detection of anomalies or defects. Moreover, this platform serves as a comprehensive solution for real-time event analysis, featuring custom analyzers specifically designed for web analytics and Industry 4.0, thus significantly improving decision-making processes across different sectors. By integrating diverse data streams and providing actionable insights, LogIsland empowers businesses to respond swiftly to changing conditions in their operational environment.

What is IBM Db2 Event Store?

IBM Db2 Event Store is a cloud-native database solution meticulously crafted to handle extensive amounts of structured data stored in Apache Parquet format. The architecture of this system is tailored to enhance event-driven data processing and analytics, allowing it to gather, assess, and store more than 250 billion events every single day. This robust data repository is both flexible and scalable, enabling it to adjust promptly to shifting business requirements. By utilizing the Db2 Event Store service, users can create these data repositories within their Cloud Pak for Data environments, which promotes effective data governance while supporting detailed analytics. Notably, the system can quickly ingest large quantities of streaming data, achieving processing rates of up to one million inserts per second per node, which is crucial for real-time analytics that integrate machine learning functionalities. It also enables immediate analysis of data from numerous medical devices, which can enhance patient health outcomes, while providing a cost-effective approach to data storage management. With such capabilities, IBM Db2 Event Store stands out as an indispensable asset for organizations aiming to effectively harness data-driven insights for improved decision-making and operational efficiency. Ultimately, its multifaceted features empower businesses to stay ahead in a rapidly evolving data landscape.

Media

Media

Integrations Supported

Apache Kafka
Apache Spark

Integrations Supported

Apache Parquet
IBM Cloud Pak for Data

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Hurence

Company Location

France

Company Website

www.hurence.com/en/logisland-platform/

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/docs/en/cloud-paks/cp-data/3.5.0

Categories and Features

Big Data

Data Mining
Data Visualization
High Volume Processing

Log Analysis

Not specified

Categories and Features

Database

Not specified

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