Cosmos DB vs MongoDB, Know The Differences

Both Cosmos DB and MongoDB are NoSQL, or non-relational, databases. This concept means their data is stored in some format other than two-dimensional tables. Some commonly-used formats for NoSQL databases in general are documents, key-value pairs, graphs, and columns, each with different strengths and tradeoffs. Cosmos DB and MongoDB are both highly-available, scalable, globally distributed and fully-managed NoSQL databases.

Benefits and Downfalls of Cosmos DB

Cosmos DB offers a high degree of flexibility, thanks to its variety of available data models and the ability to use SQL-like queries in addition to Gremlin, Azure Tables, and MongoDB APIs when interacting with your data. While MongoDB functions only as a document database, Cosmos DB can function as document, key-value, wide column, and graph-based database. Its five consistency models (eventually consistent, consistent prefix, session, bounded staleness, and strong consistency) allow you to fine-tune your latency, and it scales quite well. It is priced according to storage and throughput.

However, this flexibility can make Cosmos DB somewhat more difficult to use at first. Understanding the various data models available to you and the intended use case of each one is key to ensuring that you are getting the most optimum performance for the price, according to your application’s specific needs. It is also only available on Microsoft Azure.

Benefits and Downfalls of MongoDB

MongoDB is strictly a document-based NoSQL database. However, it allows you to run queries against your data as if it is a SQL, key-value, or graph store, whereas Cosmos DB only allows you to run queries of the same type as the data you created. Due to the JSON-like structure of documents within MongoDB and the radically faster read and write speeds (as compared to a traditional relational database), MongoDB is an extremely popular choice for use with web applications. With a maximum allowed document size of 16MB (versus 2MB with CosmosDB), it can be a more attractive option for some teams. Using MongoDB also allows you to avoid vendor lock-in, as it can run on any cloud provider.

Teams who are used to relational databases may find MongoDB difficult to get used to, since concepts like joins as SQL users understand them don’t exist out of the box. When comparing against Cosmos DB, reads and writes tend to be slower until the document size exceeds 2MB, at which point MongoDB excels.

Getting Started

Cosmos DB and MongoDB both have strengths and weaknesses that will benefit some teams but hinder others. If your infrastructure is already on Azure, or you need the flexibility of a database that supports multiple data models, Cosmos DB is the stronger offering. If you require support for larger documents and either use another cloud provider or simply want to avoid vendor lock-in, MongoDB is the best choice.

Regardless of which database suits your needs, standing them up shouldn’t be a chore. With Pulumi, provisioning either one is a breeze in the programming language of your choce. Try deploying an AKS (Azure Kubernetes Service) application with Cosmos DB or get started with MongoDB Atlas

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