STACKIT MongoDB is a fully managed MongoDB database service which automates maintenance, patching and updates. It is fully compatible to native MongoDB database, the most popular NoSQL database for modern apps.
MongoDB is a cross-platform document-oriented database program. Classified as a NoSQL database program which uses JSON-like documents with optional schemas. You can learn more about it in the official documentation of MongoDB.


  • Scalability: You can scale your database in a vertical way. That means, that you can add more vCPU, vRAM or more disk space to your database.
  • High security data access and storage: RBAC authorization, TLS 1.3 and STACKIT Object Storage make sure that your data and backups are accessed and stored securely.
  • Real-time analytics: With the customer dashboard you are able to track your workload on the database to see the performance.
  • Replication: With the replica set of three nodes the database replicates its data to all of the nodes making the system failure proof.
  • Accessibility: STACKIT MongoDB service is available with a public IP address within the Cloud Foundry and outside, so that they may also be combined with Kubernetes workloads or Virtual Machines.
  • Data queries: You may use CRUD operations to create, read, update, and delete documents.
  • Modeling data: Data modeling is also supported, so that you may access and manage your data efficiently.
  • Data aggregation and transformation: Mongoimport enables you to import BSON, JSON, CSV and TSV files and aggregation pipelines let you aggregate and transform data easily.

Use cases

Popular use cases for MongoDB are the following:

  • Single View of Anything: Aggregate and transform data for your application e.g. having a view of your real-time retail prices, as well as storing your historical customer behaviour.
  • Internet of Things: Due to the multitude of sensor types and data used in IoT devices your database needs to be able to support flexible data schemas and be able to adjust it for future changes.
  • Personalisation Engines: Create a customer-tailored experience through targeted display of options and products through the analysis of preconfigured profiles and/or historical data and preferences.
  • Catalog: Create a product catalog with different offerings and prices based on different factors such as location.
  • Analytics: Big data analysis through aggregation pipelines e.g. creating a sales report of multiple income channels such as different store locations.
  • Content management: Store and serve information of and for different websites and applications such as blogs.