MongoDB and Embarcadero Technologies: Model Your Big Data

With round-trip database support, data modeling professionals can use ER/Studio® Data Architect to easily reverse-engineer, compare and merge, and visually document data assets residing in diverse locations from data centers to mobile platforms. A variety of database platforms, including traditional RDBMS and non-relational technologies such as MongoDB, can be imported and integrated into shared models and metadata definitions.

MongoDb

ER/Studio Data Architect includes the capability to natively reverse engineer MongoDB databases into an entity relationship diagram, as well as providing a means to forward engineer into blank-sample JSON. Access to the MongoDB assets can be controlled with Kerberos and SSL authentication and encryption. The integrated wizard menus allow the selection of specific tables and their properties to be manipulated, for granular visibility of the data.

ER/Studio's comprehensive model management and collaboration capabilities simplify the tasks of building and maintaining complex enterprise data models. Its easy-to-use visual interface helps data architects to document, understand, and publish information about diverse data sources and databases so they can be better harnessed to support business objectives.

Data Architect enables modelers to create and compare models from existing databases and ensure consistency between data models. With a data modeling strategy in place, enterprise data can be more effectively leveraged as a corporate asset, while supporting compliance to business standards and mandatory regulations – essential factors in an organization's data governance program.

Watch this short video to see how MongoDB databases can be reverse engineered using ER/Studio Data Architect:

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Reverse engineer a MongoDB database


"ER/Studio's big competitive advantage is its ease of use. Whether you want the product for data modeling per se, or you just want to document your existing system, this ease of use should be a major factor."
- Bloor Research