Microsoft Azure Cosmos DB is Microsoft's Big Data analysis platform. It is a NoSQL database service and is a replacement for the earlier DocumentDB NoSQL database.
N/A
MongoDB
Score 8.8 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Azure SQL Database
Score 8.4 out of 10
N/A
Azure SQL Database is Microsoft's relational database as a service (DBaaS).
$0.50
Per Hour
Pricing
Azure Cosmos DB
MongoDB
Azure SQL Database
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
2 vCORE
$0.5044
Per Hour
6 vCORE
$1.5131
Per Hour
10 vCORE
$2.52
Per Hour
Offerings
Pricing Offerings
Azure Cosmos DB
MongoDB
Azure SQL Database
Free Trial
No
Yes
No
Free/Freemium Version
No
Yes
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
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More Pricing Information
Community Pulse
Azure Cosmos DB
MongoDB
Azure SQL Database
Considered Multiple Products
Azure Cosmos DB
Verified User
Engineer
Chose Azure Cosmos DB
Azure Cosmos DB is a fully managed NoSQL database & globally distributed NoSQL database service. Its very fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development DB platform compare to MongoDB.
Azure Cosmos DB has the benefit of having multi-master key tenancy compared to Redis and Mongo. Reads are just as fast, if not faster than Mongo. However, the distribution of writes (i.e. ACID transactions) isn't as high as Google Cloud Spanner or CouchDB. Azure Cosmos DB …
Because we often use Microsoft products for large corporate projects and other customer projects, and compatibility and integration are important to us, we used this platform, which in addition to very high security, has a very good response speed, also, building modern …
We evaluated Mongo DB and Amazon Redshift. In the end, we decided to have both Redshift and Cosmos but for different app stacks. For apps hosted on Azure, Cosmos plays a very important role. Also from a support standpoint, Microsoft offers very good service and an equally good …
Our development and administration teams are just more familiar with the Microsoft Stack, and there was very little additional knowledge required to put this into production.
Cosmos DB is unique in the industry as a true multi-model, cloud-native database engine that comes with solutions for geo-redundancy, multi-master writes, (globally!) low latency, and cost-effective hosting built in. I've yet to see anything else that even comes close to the …
The flexible structure underlying MongoDB's construction is not found in other competitors; the ability to easily change the structure without affecting other stored documents. It is very ideal for projects that you cannot predict that the structure will change this way. Of …
MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most …
Amazon's RDS offering is actually very good and is used in other parts of the company, we just have a lot of Azure experience so wanted to leverage that.
Like any NoSQL database, whether it's MongoDB or not, it's best suited for unstructured data. It's also well suited for storing raw data before processing it and performing any type of ETL on the data.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
We have found it's a great alternative for making older legacy applications work with online databases instead of only on-premises databases. We've converted over a dozen applications this way, and it has allowed our clients to have a distributed workforce using their applications without incurring the expense of a complete application rewrite.
Scalable Instantly and automatically serverless database for any large scale business.
Quick access and response to data queries due to high speed in reading and writing data
Create a powerful digital experience for your customers with real-time offers and agile access to DB with super-fast analysis and comparison for best recommendation
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
Maintenance is always an issue, so using a cloud solution saves a lot of trouble.
On premise solutions always suffer from fragmented implementations here and there, where several "dba's" keep track of security and maintenance. With a cloud database it's much easier to keep a central overview.
Security options in SQL database are next level... data masking, hiding sensitive data where always neglected on premise, whereas you'll get this automatically in the cloud.
We had a thought time migrating from traditional DBs to Cosmos. Azure should provide a seamless platform for the migration of data from on-premises to cloud.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
One needs to be aware that some T-SQL features are simply not available.
The programmatic access to server, trace flags, hardware from within Azure SQL Database is taken away (for a good reason).
No SQL Agent so your jobs need to be orchestrated differently.
The maximum concurrent logins maybe an unexpected problem.
Sudden disconnects.
The developers and admin must study the capacity and tier usage limits https://docs.microsoft.com/en-us/azure/azure-subscription-service-limits otherwise some errors or even transaction aborts never seen before can occur.
Only one Latin Collation choice.
There is no way to debug T-SQL ( a big drawback in my point of view).
It's efficient, easy to scale, and works. We do have to do a bit of administration, but less now than when we started with this a couple of years ago. Microsoft continues to improve its self-management capability.
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
It has very good compatibility and adaptability with other APIs and developers can safely create new apps because it is compatible with various tools and can be easily managed and run under the cloud, and in terms of security, it is one of the best of its kind, which is very powerful and excellent.
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
The interfaces are intuitive once you are familiar with all the functions. The ability to use different tools to interact with the platform, such as directly via a browser or code editors such as VS Code or Visual Studio is a great option and allows for integrating withn the project and other testing and developing tools.
Microsoft is the best when it comes to after-sales support. They have a well-structured training and knowledge base portal that anyone can use. They are usually quick to respond to cases and are on point for on-call support. I have no complaints from a support standpoint. Pretty happy with the support.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
We give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
Cosmos DB is unique in the industry as a true multi-model, cloud-native database engine that comes with solutions for geo-redundancy, multi-master writes, (globally!) low latency, and cost-effective hosting built in. I've yet to see anything else that even comes close to the power that Cosmos DB packs into its solution. The simplicity and tooling support are nice bonus features as well.
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
We moved away from Oracle and NoSQL because we had been so reliant on them for the last 25 years, the pricing was too much and we were looking for a way to cut the cord. Snowflake is just too up in the air, feels like it is soon to be just another line item to add to your Azure subscription. Azure was just priced right, easy to migrate to and plenty of resources to hire to support/maintain it. Very easy to learn, too.
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB