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
Neo4j
Score 8.8 out of 10
N/A
Neo4j is an open source embeddable graph database developed by Neo Technologies based in San Mateo, California with an office in Sweden.
$65
per month
Microsoft SQL Server
Score 8.6 out of 10
N/A
Microsoft SQL Server is a relational database.
$1,418
Per License
Pricing
MongoDB
Neo4j
Microsoft SQL Server
Editions & Modules
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Aura Professional
$65
per month
Community Edition
Free
Enterprise Edition
Contact Sales
Aura Free
Free
Aura Enterprise
Contact Sales
Subscription
$1,418.00
Per License
Enterprise
$13,748.00
Per License
Offerings
Pricing Offerings
MongoDB
Neo4j
Microsoft SQL Server
Free Trial
Yes
Yes
No
Free/Freemium Version
Yes
Yes
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
Fully managed, global cloud database on AWS, Azure, and GCP
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Community Pulse
MongoDB
Neo4j
Microsoft SQL Server
Considered Multiple Products
MongoDB
Verified User
Employee
Chose MongoDB
Also, using DocumentDB, and both are good, each was chosen based on the developer's expertise. So take advantage of in-house skills.
There are use cases for both relational and non-relational databases. MongoDB is simply a different method of storing data, but I find it to be faster and more intuitive than relational models.
MongoDB was the most full-featured NoSQL database we evaluated - that offered atomic transactions at a document level, built-in HA & DR, open source, robust queries, and enterprise level support.
Other platforms had specific parts of what we were looking for - MongoDB had it all.
I selected MongoDB because it works for well with web interfaces. All of the RDBMS alternatives would have required a lot more time writing schemas and working around retrieving data and mapping it. That could have been somewhat mitigated with Entity Framework, but that again …
Verified User
Project Manager
Chose MongoDB
MongoDB is document oriented, and fits our goals best.
Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join …
Neo4j is ahead of any of the leading competitors I know. The only one which comes close, in my opinion, is the "Titan-Distributed Graph Database" which is completely open source and free to use. Titan works on top of Apache Cassandra so it has some huge learning curves to do, …
Microsoft SQL server is easy to use and to access by everyone, (new users), can learn very easily. Most of our company uses SQL Server because it uses and joins with one of the best commands used in the industry. With MongoDB we can't use the joins so this is the plus point in …
Microsoft SQL Server is a comprehensive solution as transactional database, data warehouse, analytics, reporting, and ETL. It also integrates with the cloud well (Azure). The ease of use and setup makes this better than Oracle Database because the query syntax is also different …
Microsoft SQL Server is one of the fastest RDBMS systems available in the market. Pricing is a bit on the higher side but all the features it provides pretty much justifies it. It can be integrated with a large number of frameworks thus enabling to work on multiple frameworks …
Microsoft SQL Server is still the industry standard for the type of development we do, and the types of applications that we use. Almost every developer or analyst we hire has at least a reasonable grounding in the use of SQL servers, and it is almost universally compatible …
SQL Server is better for large databases containing structured relational data. It makes it easy to group and order, to sum and create tables of data from any data stored in a table or related tables. While Dynamodb is very good at STORING huge amounts of unstructured data, it …
SQL Server is way ahead of the support available and documentation available. Oracle should invest heavily in bringing good technical books on MySQL rather than putting documentation online and expect users to go through it.
Easy to manage all tools without extra cost is a big …
Microsoft SQL Server is more secure and offers more robustness for our data. SQL Server is also great because of its integration with Microsoft Visual Studio. It's also great because developers can build reports and stuff like that from scratch. It's faster compared to PostgreSQ…
Microsoft is more appropriate for the requirements of this particular organisation due to its ability to handle structured data efficiently and the fact that it is already widely used.
I have been a SQL Server focused professional for over 20 years, so SQL Server is my first choice. I have experience and comfort, and the ability to get up to speed quickly. Oracle has been too expensive, though I think it has performed similar to SQL Server in the applications …
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.
Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using Tableau, for example.
Microsoft SQL is ubiquitous, while MySQL runs under the hood all over the place. Microsoft SQL is the platform taught in colleges and certification courses and is the one most likely to be used by businesses because it is backed by Microsoft. Its interface is friendly (well, as pleasant as SQL can be) and has been used by so many for so long that resources are freely available if you encounter any issues.
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.
Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios.
Native support for REST API, that makes interacting with Neo4J intuitive and easy.
Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language.
Nice UI and interface for executing the Query and visualizing the response.
UI access controlled by User credentials allows for neat access controls.
Awesome free community edition for small-scale projects.
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 of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution.
Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API.
There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software.
Microsoft SQL Server Enterprise edition has a high cost but is the only edition which supports SQL Always On Availability Groups. It would be nice to include this feature in the Standard version.
Licensing of Microsoft SQL Server is a quite complex matter, it would be good to simplify licensing in the future. For example, per core vs per user CAL licensing, as well as complex licensing scenarios in the Cloud and on Edge locations.
It would be good to include native tools for converting Oracle, DB2, Postgresql and MySQL/MariaDB databases (schema and data) for import into Microsoft SQL Server.
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.
We understand that the Microsoft SQL Server will continue to advance, offering the same robust and reliable platform while adding new features that enable us, as a software center, to create a superior product. That provides excellent performance while reducing the hardware requirements and the total cost of ownership of our solution.
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.
Learning cypher was super easy coming from a SQL background. Furthermore, the docs Neo4j provides on their website make it really easy to pull up a reference, guide or a quick example. The mac app they provide is also really well designed with good visualisation tools, with the ability to easily use colour, line thickness etc to help navigate your data.
SQL Server mostly 'just works' or generates error messages to help you sort out the trouble. You can usually count on the product to get the job done and keep an eye on your potential mistakes. Interaction with other Microsoft products makes operating as a Windows user pretty straight forward. Digging through the multitude of dialogs and wizards can be a pain, but the answer is usually there somewhere.
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 managed to handle most of our problems by looking into Microsoft's official documentation that has everything explained and almost every function has an example that illustrates in detail how a particular functionality works. Just like PowerShell has the ability to show you an example of how some cmdlet works, that is the case also here, and in my opinion, it is a very good practice and I like it.
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.
Other than SQL taking quite a bit of time to actually install there are no problems with installation. Even on hardware that has good performance SQL can still take close to an hour to install a typical server with management and reporting services.
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.
Neo4j is a graph store and has different use cases compared to another NoSQL Document store like MongoDB. MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive. MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to MongoDB yet, whereas Neo4J is ACID complaint with all its operations.
[Microsoft] SQL Server has a much better community and professional support and is overall just a more reliable system with Microsoft behind it. I've used MySQL in the past and SQL Server has just become more comfortable for me and is my go to RDBMS.
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
Increased accuracy - We went from multiple users having different versions of an Excel spreadsheet to a single source of truth for our reporting.
Increased Efficiency - We can now generate reports at any time from a single source rather than multiple users spending their time collating data and generating reports.
Improved Security - Enterprise level security on a dedicated server rather than financial files on multiple laptop hard drives.