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Learn MorePros of Azure Cosmos DB
Pros of MongoDB Atlas
Pros of Azure Cosmos DB
- Best-of-breed NoSQL features28
- High scalability22
- Globally distributed15
- Automatic indexing over flexible json data model14
- Tunable consistency10
- Always on with 99.99% availability sla10
- Javascript language integrated transactions and queries7
- Predictable performance6
- High performance5
- Analytics Store5
- Rapid Development2
- No Sql2
- Auto Indexing2
- Ease of use2
Pros of MongoDB Atlas
- MongoDB SaaS for and by Mongo, makes it so easy9
- Amazon VPC peering6
- MongoDB atlas is GUItool through you can manage all DB4
- Granular role-based access controls4
- Built-in data browser3
- Use it anywhere3
- Cloud instance to be worked with3
- Simple and easy to integrate1
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Cons of Azure Cosmos DB
Cons of MongoDB Atlas
Cons of Azure Cosmos DB
- Pricing17
- Poor No SQL query support4
Cons of MongoDB Atlas
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What is Azure Cosmos DB?
Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.
What is MongoDB Atlas?
MongoDB Atlas is a global cloud database service built and run by the team behind MongoDB. Enjoy the flexibility and scalability of a document database, with the ease and automation of a fully managed service on your preferred cloud.
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What companies use Azure Cosmos DB?
What companies use MongoDB Atlas?
What companies use Azure Cosmos DB?
What companies use MongoDB Atlas?
See which teams inside your own company are using Azure Cosmos DB or MongoDB Atlas.
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What tools integrate with Azure Cosmos DB?
What tools integrate with MongoDB Atlas?
What tools integrate with Azure Cosmos DB?
What tools integrate with MongoDB Atlas?
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What are some alternatives to Azure Cosmos DB and MongoDB Atlas?
Azure SQL Database
It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Neo4j
Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.