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mongoDB Reviews
45 reviews
- 01 What is mongoDB?
- 02 Pros and cons from reviewers
- 03 Main features
- 04 How mongoDB compare to similar software?
- 05 Who is mongoDB best for according to our reviewers?
- 06 mongoDB Reviews
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01 What is mongoDB?
MongoDB is a database management system that provides a range of features to help businesses grow by enabling faster and smarter creation. It offers a flexible document data model and a unified query interface for all use cases, allowing for faster development and iteration. MongoDB is cloud-managed, making it scalable and ideal for startups. It can be used for various transactional, analytical, and data virtualization applications. The platform can be run anywhere, anytime, even on a simple laptop. It also prioritizes data security with ISO/IEC 27 001 and HDS certifications. Many companies, including Bosch, Cisco, Toyota, and Humanitix, use MongoDB due to its performance and relevance.
02 Pros and cons from reviewers
Pros from reviewers
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Secure data storage
MongoDB offers high security for data storage, ensuring that your data is safe and manageable -
Easy to learn
MongoDB is user-friendly and easy to learn, making it a great choice for beginners and experts alike -
High performance
MongoDB is known for its high performance, speed, and efficiency, making it a great choice for managing large amounts of data. -
Cloud solution
MongoDB's Atlas Cloud allows for easy integration of a single database across multiple apps, with user-friendly management and affordable cost -
Document orientation
MongoDB's document-oriented nature makes it an excellent choice for handling various types of data needs, especially for applications that require a flexible schema
Cons from reviewers
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Issues with complex data
Some users have found that dealing with complex data can be difficult in MongoDB, particularly when it comes to updating collection indexing and managing memory usage -
Inferior client tool
Some users have found the Compass client tool to be inferior compared to other database software tools, with most of the access to the collections being CLI-based. -
Problems with Atlas Compass UX
Users have reported issues with the Atlas Compass UX, such as not being able to open multiple tabs with collections at the same time and losing search queries when switching between collections -
Poor customer support
There have been complaints about MongoDB's customer support being non-existent or unhelpful, even for minor technical issues -
Limited memory in the free version
Users have reported that the free version of MongoDB has limited memory, which can necessitate an upgrade for unlimited data insertion
mongoDB
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03 Main features
Starting Price
Free Plan
Find and view your data easily
Make your databases evolve with the demand
Automate your administrative operations
Integrated security
Deploy your data in different clouds
More details about mongoDB plans
Starting Price
Free Plan
Yes
Find and view your data easily
Make your databases evolve with the demand
Automate your administrative operations
Integrated security
Deploy your data in different clouds
mongoDB
Premium
Boost your productivity with a database optimized for your applications
$500 in credits for 1 year
Save up to $500
04 How mongoDB compare to similar software?
Firebase and MongoDB are powerful platforms for managing databases, each offering valuable features that can significantly enhance your application's backend. However, there are several key differences to consider when deciding which is best for your project.
First is the architecture. Firebase is a Backend-as-a-Service (BaaS) platform that provides a real-time NoSQL database known as Firestore. It is designed to offer seamless data synchronization across clients, real-time updates, and integration with various Google services, making it ideal for developing mobile and web applications quickly. On the other hand, MongoDB is a NoSQL database that uses a flexible document-oriented model, which allows developers to store data in JSON-like documents. MongoDB excels in handling large volumes of unstructured data, complex queries, and providing scalability through sharding and replication.
When it comes to pricing, Firebase offers a pay-as-you-go model, starting with a free tier that...
mongoDB
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Boost your productivity with a database optimized for your applications
$500 in credits for 1 year
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05 Who is mongoDB best for according to our reviewers?
-
Developers working with Node.js
These users appreciate MongoDB for its simplicity when querying JSON-like data, making it a preferred choice for Node.js application development. However, they note that the non-tabular structure can complicate the application of joins using aggregation -
Data Warehousing Professionals
These users have used MongoDB to build multi-node clusters for data warehousing and ETL tools. They acknowledge that while MongoDB has improved over time, it may not offer as robust backups as other databases like MSSQL and Oracle -
Users managing large data entries
These users value MongoDB for managing websites with thousands of data entries. They appreciate its speed and simplification of object-oriented data storage, but note that its global adoption isn't as widespread as other databases, which can limit online resources. -
Users dealing with variable length and semi-irregular data
These users find MongoDB to be a reliable solution for hosting incoming user data with variable lengths and semi-irregular formats. They appreciate its easy implementation and reliability, but note challenges with data visualization and connectivity with AWS VPC -
Users needing a database for microservices applications
These users find MongoDB to be the top choice for microservices applications due to its scalability, user-friendliness, and integrations with popular programming languages. They caution that as a NoSQL database, it may be challenging for beginners
mongoDB
Premium
Boost your productivity with a database optimized for your applications
$500 in credits for 1 year
Save up to $500
06 mongoDB Reviews
mongoDB rating
mongoDB Reviews
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Vern Pollich
Natural Fit for Nested Data and Powerful Aggregations
What I appreciate most is how easy it is to work with nested JSON-like data in MongoDB. For event tracking and user activity logs, it feels much more natural than forcing everything into a relational schema, and the aggregation pipeline has been more useful than I expected for reporting
June 1, 2026
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Gertha Cummings
Flexible Document Modeling for Product Catalogs
MongoDB has been a good fit for our product catalog because the document model lets us store different item attributes without redesigning tables every time the business team adds a new field. Indexing took some trial and error, but once we tuned a few queries the performance was solid
May 25, 2026
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Jarod Herman
Credits Enable Proper Dev/Staging/Prod Separation
indexing and relevance tuning took a bit of trial and error, but once set up it simplified our architecture
May 17, 2026
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Maye Sawayn
Predictable Multi-Document Transactions
that breathing room let us test search indexes and backups properly before committing to a long-term tier
May 10, 2026
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Shirley Bruen
Atlas Search without Running Elasticsearch
We got $3,600 in MongoDB credits for Startups through Joinsecret and it covered our first few months of Atlas while we tuned the cluster size
May 4, 2026
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Haywood Smith
Startup Credits to Tune Atlas Risk-Free
The developer experience is good: Compass is handy for quick inspections, and the Node driver feels mature, but the real win for us was schema validation in the collection so we get flexibility without letting garbage documents creep in
April 26, 2026
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Lila Harris
Strong Dev Tools plus Schema Validation Guardrails
Realm and Atlas Triggers saved us time for small background tasks like syncing to Slack and cleaning up orphaned records, and the change streams integration made it straightforward to build real-time updates without polling
April 20, 2026
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Christie O'Keefe
Realm, Triggers & Change Streams for Real-Time Automation
I like how the aggregation pipeline lets us keep a lot of reporting logic close to the data, and with $lookup plus $facet we replaced a bunch of application-side post-processing, though you do need to watch memory limits and design pipelines carefully
April 12, 2026
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Gavin Boyer
Powerful Aggregation for In-DB Reporting
We moved a high-write workload to a sharded cluster and the scaling story has been solid, plus the compound indexes and TTL indexes keep the data tidy without nightly jobs
April 7, 2026
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Tyron Windler
Sharded Scaling for High-Write Workloads
the metrics and slow query insights helped us find a couple of bad indexes fast, and the document model fits our event payloads better than forcing them into rigid tables
March 31, 2026
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