Features

Overview of all SmartCMDB functions

Flexible Data Model

The CMDB can be adapted flexibly and standardized to your individual needs. See at a glance what is important to you.

Flexible Data Model

The data organization of the Smart CMDB has a uniquely flexible structure. All objects in the database display CIs (configuration elements). This highly flexible data model enables all CIs (e.g. hardware, users, tickets, etc.) with their attributes and relations to be related to each other in any way. The Smart CMDB is able to adapt individually to your structures by freely defining the CI types and their attributes. Since the CMDB database is available in normalized form, it is particularly easy to build individual CMDB structures.

Furthermore, the Smart CMDB contains predefined structure trees for standard contexts (e.g. hardware, software, etc.). These can be used “ready-to-use”, modified or even discarded. Intelligent inheritance concepts, an extensive authorization system and consistent lifecycle models simplify the structure and operation of the smart CMDB considerably.

Auto-Discovery

Auto-Discovery fills your CMDB fully automatically. The integrated monitoring continuously records status information and changes. All objects, their properties and status are thus always up-to-date and centrally available.

Cloud Asset Discovery

With Cloud Asset Discovery, data from the various components of your cloud provider (Azure, Google, AWS, etc.) can be easily read out. The data is stored as CIs in the SmartCMDB according to a defined mapping structure.

Manual Import

REALTECH SmartCMDB has standard import functions for various data formats (e.g. XML, Excel, CMDBf) in combination with efficient mapping functionality.

Mapping

The REALTECH SmartCMDB has a mapping functionality for the unambiguous assignment of data and status information from external data sources to the CIs and attributes in the CMDB.

Normalization

The CMDB normalizes or standardizes all infrastructure data that is scanned and captured by Auto-Discovery. Thus, data and information of a heterogeneous IT infrastructure data can be compared and evaluated immediately.