System description

web-based, modular, scalable, flexible – eguide4DATA

The system consists of the APP eguide4DATA, the eguide4DATA Agent and the connected archives. The APP manages archives, users, versions, revisions and backups, while the agent is responsible for check-in, check-out, the Open Editor, comparisons and the creation of backups/images.

The app is web-based and therefore accessible on all end devices. Another advantage is that no client installation is required. The app interface is an all-in-one interface that can be used to carry out all activities in the web interface. Depending on the licence and user rights, different information can be displayed in the app. It is also possible for several administrators to work in the software at the same time without any restrictions.

The app can manage an unlimited number of archives, allowing data from different production areas or locations to be cleanly separated from each other. The archives can be connected in a variety of ways. eguide4DATA supports the following communication protocols depending on the archive type: SMB, FTP, SFTP and S3 (Amazon protocol). For SFTP, eguide4DATA supports various authentication methods, including the use of private keys, SSH agents and user name/password combinations.

The way in which the customer can host the software is also flexible. eguide4DATA can be operated either on-premise, in a cloud or as a cluster installation.

Communication takes place via web socket communication, which is initiated by the agent and then enables bidirectional information exchange between the app and the agent.

Communication between the web frontend and the backend takes place via an SSL-encrypted connection. Communication between the agent and the web app is also encrypted and important information such as passwords are stored in the database in encrypted form.

The system uses two databases: an SQL database for standard topics such as comments, comparisons and users, and a NoSQL database that is used exclusively for the analytics module to ensure efficient processing of large volumes of data.