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Description

IBM Db2 Event Store is a cloud-native database system specifically engineered to manage vast quantities of structured data formatted in Apache Parquet. Its design is focused on optimizing event-driven data processing and analysis, enabling the system to capture, evaluate, and retain over 250 billion events daily. This high-performance data repository is both adaptable and scalable, allowing it to respond swiftly to evolving business demands. Utilizing the Db2 Event Store service, users can establish these data repositories within their Cloud Pak for Data clusters, facilitating effective data governance and enabling comprehensive analysis. The system is capable of rapidly ingesting substantial volumes of streaming data, processing up to one million inserts per second per node, which is essential for real-time analytics that incorporate machine learning capabilities. Furthermore, it allows for the real-time analysis of data from various medical devices, ultimately leading to improved health outcomes for patients, while simultaneously offering cost-efficiency in data storage management. Such features make IBM Db2 Event Store a powerful tool for organizations looking to leverage data-driven insights effectively.

Description

The LogIsland platform serves as the core of Hurence's real-time analytics system, enabling the collection of factory events from the IIoT as well as data from websites. Hurence asserts that both factories and companies can be monitored and understood in real time through the myriad of events they experience, where each occurrence, such as a sales order, the production of an item by a robot, or the delivery of a product, qualifies as an event. Essentially, everything constitutes an event, and the LogIsland platform facilitates the capture of these events, organizing them within a message bus capable of handling substantial volumes. This system allows for real-time analysis with a range of plug-and-play analyzers that vary from basic functions like counting and alerting to advanced artificial intelligence models designed for predictive analytics and the identification of anomalies or defects. It stands as your versatile tool for real-time event analysis, equipped with custom analyzers tailored for two specific areas: web analytics and Industry 4.0, thereby enhancing decision-making processes across various domains.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Kafka No 
Apache Parquet Yes 
Apache Spark No 
IBM Cloud Pak for Data Yes 

Integrations

Apache Kafka Yes 
Apache Parquet No 
Apache Spark Yes 
IBM Cloud Pak for Data No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

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

Vendor Details

Company Name

Hurence

Country

France

Website

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

Product Features

Database

Backup and Recovery No 
Creation / Development No 
Data Migration No 
Data Replication No 
Data Search No 
Data Security No 
Database Conversion No 
Mobile Access No 
Monitoring No 
NOSQL No 
Performance Analysis No 
Queries No 
Relational Interface No 
Virtualization No 

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining Yes 
Data Visualization Yes 
Data Warehousing No 
High Volume Processing Yes 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

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