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What is Mnesia?

In the realm of telecommunications, data management involves a range of components that are not entirely addressed by conventional Database Management Systems (DBMSs). Recognizing the crucial need for high fault tolerance in systems that require continuous operation, as well as the requirement for the DBMS to function within the same address space as the applications, we introduced an innovative DBMS called Mnesia. Mnesia is deeply intertwined with Erlang, providing key features necessary for constructing fault-tolerant telecommunications systems. Tailored specifically for industrial-grade telecommunications applications, Mnesia functions as a multiuser distributed DBMS, with Erlang serving as its core programming language. This system is designed to tackle the diverse data management challenges typically faced in telecommunications environments and includes several sophisticated features that are often absent in traditional DBMSs. Furthermore, the architecture of Mnesia prioritizes both reliability and performance, positioning it as an optimal solution for mission-critical applications in the telecommunications sector. As such, Mnesia not only meets existing demands but also anticipates future needs in data management within the industry.

What is Esper Enterprise Edition?

Esper Enterprise Edition presents a powerful platform that is engineered for both linear and elastic scalability, along with dependable event processing that is resilient to faults. The platform features an EPL editor and debugger, supports hot deployment, and offers extensive reporting on metrics and memory usage, including in-depth analyses per EPL. Moreover, it includes Data Push capabilities for smooth multi-tier delivery from CEP to browsers, effectively managing both logical and physical subscribers along with their subscriptions. The user-friendly web interface enables users to monitor numerous distributed engine instances utilizing JavaScript and HTML5 while facilitating the design of composable and interactive visualizations for distributed event streams through charts, gauges, timelines, and grids. In addition, it boasts JDBC-compliant client and server endpoints to guarantee seamless interoperability across various systems. Esper Enterprise Edition stands out as a proprietary commercial product crafted by EsperTech, with source code access provided exclusively for customer support. This impressive array of features and its adaptability render it an exceptional option for enterprises in search of effective event processing solutions. As businesses evolve and their needs become more complex, having a solution like Esper can significantly enhance their operational efficiency.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Erlang

Date Founded

1997

Company Website

erlang.org/doc/apps/mnesia/Mnesia_chap3.html

Company Facts

Organization Name

EsperTech Inc.

Company Location

United States

Company Website

www.espertech.com/esper-enterprise-edition/

Categories and Features

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Categories and Features

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

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