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MongoDB serves as a local dev database and as a production database for some of our microservice solutions. We use it for front-end-heavy projects and storing document based data, where original RDBMS solution would be overkill.
- Document-based information storing and retrieving.
- Indexing and querying small documents from a big heap of files.
- Integrating with JS-based backend.
- By design, joined collections tend to be much slower than in relational DB.
- Some kind of relational model support.
February 28, 2020
We use MongoDB at the heart of our application where speed and consistency are critical. It's used primarily by the engineering backend team and vicariously by other teams using parts of the product. It gives us the means to quickly iterate our data models with fewer painful migrations than we'd have with a traditional RDBMS and its JSON-like BSON object modeling maps nicely to our APIs.
- The BSON-based document storage models allow for sophisticated data modeling.
- Flexible MongoDB collection schemas allow for the storage of polymorphic records and easy migrations.
- MongoDB has readily adopted popular database concepts like change streams and graph queries.
- MongoDB will start to struggle with very large datasets even when well-indexed.
- Complex aggregation queries can be tricky in MongoDB when compared with an SQL-based database.
- Scaling a Mongo database can be expensive.
February 26, 2020
We use MongoDB as a database for all web and mobile applications developed for our customers. It fully meets our needs. Reliable, handy, and robust, the support is of high quality. The installation on our servers is very easy. Its management and maintenance are easy and fast. MongoDB gives us satisfaction, and our customers are happy.
- Mongo DB is free for commercial use
- MongoDB is very fast for data processing.
- Very easy to learn and use.
- JSON responses are particularly handy in a full-stack Javascript environment.
- A more user-friendly user management tool would be a good thing.
February 26, 2020
We use MongoDB as our main operational data store. The application writes directly to the database. We further use it to provide operational reports to our end-users.
- Flexible schema for changing data elements.
- Sharding and replication are seedless.
- Setting triggers instead of change stream watcher.
- Slowly changing dimension equivalent would be nice.
MongoDB is currently being used to structure our databases and our primary querying tool. What is convenient about it is that you can change tables without writing lots of code. All data is stored in javascript, which is what all of our programmers use, so the gap between data analysis and our developers is lessened.
- Schema-less database, which means easy to scale.
- Easy indexing gives better query times.
- Not a relational database. Lots of capabilities lost here.
- No joins, which is new to me.
So this the non-relational Database that we have internally. The reason for using this is because of the amazing scalability that this database provides and the JSON file format in which it tends to store the data that is present within it. Its opensource and that is the reason we have been using it internally to store the git hashes of the manifest since there are millions of them getting generated every month and we need a method to scale to that extent.
- NoSQL
- Scalability
- Readable queries
- Opensource
- None so far, but security issues have occurred
February 26, 2020
We use MongoDB as our primary backend data store solution for our products. We decided to use NoSQL for our project, and MongoDB's document-oriented approach fits our needs and data model very well. It is well supported by many cloud vendors and has been a pleasure to work with for our developers.
- Great support by most cloud platform vendors
- Great developer experience
- Easy to set up locally for local development, troubleshooting, etc.
- Excellent library support for popular programming languages
- Document oriented approach is excellent for data models that can be naturally represented in this way.
- Unlike SQL, MongoDB has no joins, which can be an issue in some data retrieval cases, making it less optimal.
- Not 100% ACID compliant (MongoDB 4 is making improvements, however), although this is also one of the reasons for MongoDB's strength, it would require you to think through your use cases more.
- The aggregation has a bit of a learning curve.
February 26, 2020
Our Denver Development team is using MongoDB in an application they wrote, and it's collecting big data associated with the application's users. A SQL Server was formerly capturing this type of data and that's not a great platform for big data. They set it up, configured it, and got it working, all I have to do is the administration work required by SOX.
- We're using it to capture/store big data
- Easy setup and configuration by developers
- The administrative interface isn't terrific, but it does work.
March 02, 2020
This tool has been used project-wise for the projects in which real-time data is used for analysis. We use this tool for fetching the comments on the products on social media to understand the sentiments of the end-user. The data is real-time and unstructured so we use this tool to make our work easy.
- Reads real-time data very accurately and fast.
- Writing query is also pretty easy in it.
- Connection with the other tools through API's is also pretty simple.
- There are no in-built analytics functions in it.
- If the data is of similar type then it is very difficult to remove the same comments.
- In the cloud environment sometimes it works very slow.
December 12, 2019
Using MongoDB as a potential solution for NoSQL data storage and quick application prototyping. It is an enterprise approved NoSQL solution. My investigation into the product and use of it is for innovation type activities.
- Schema-less data models.
- High performance.
- Aggregation can be a little hard to learn.
August 26, 2019
I am using MongoDB as our database back-end system. It's an efficient NoSQL for scalability. The support is good and new features were added in every release. Documentation is helpful and complete for many use cases.
- Horizontal scaling with shard cluster
- Helpful documentation
- New and meaningful features in yearly releases
- Aggregation framework for reporting application
- Transaction not supported on sharded collection
- Documentation is complete but not well structured
- Support for MongoDB customers should be improved
I am using it for my software development back-end system. All of my programmers also use this for the same reason. Its's very latest and efficient platform for developing applications. We can easily learn it from its official website and understand quickly. very easy query languages are available on this system. So we can access this.
- Very easy query languages.
- Less time needed to understand it.
- Very easy installation.
- Very fast for data inserting.
- Transaction function not available.
- Memory consumption is high.
March 14, 2019
MongoDB was our main data store used primarily by a web application managing classical relational entities as well as some big data and analytics collection data. Even though no one on the team had much DB experience MongoDB was easy to use and integrate. However, we faced many pitfalls along the way and the end result was far from optimal.
- Easy to set up locally and on different SAAS providers (Compose.io and then MongoDB atlas).
- Being schema-less helped with having a rapid pace of development as there where many schema changes.
- Full stack developers on a NodeJS server could get started very fast as the API was familiar and relatively simple.
- Very hard to tell how to best structure your data and then effectively query it. Most of the time this led to just splitting everything into different collections and joining them on the application server or the client which was slow and hard to maintain.
- Documentation is not friendly and confusing.
- No real joins and complex querying is unclear.
February 28, 2019
We are using this database to store the raw JSON data as documents. We are using this to store the user's activity as a row in JSON so that we can later process that data. This tool is not being used by everyone in the company, but only a few of us.
- Good integration with the Hadoop ecosystem, so it can be used with the other services of the Hadoop ecosystem.
- A good NoSQL family database, so you can easily store the raw data as documents.
- Good scalability as you can easily share the data and have quick availability of data.
- Easy replication of the data.
- Learning will definitely take time.
- Updating is not fast, so if you have a use case where you need to update your data at a high rate, then it is not a good choice
February 22, 2019
The Engineering team uses MongoDB as our NoSQL database technology. While we do use a relational database (MySQL) as the primary data warehouse solution, we use Mongo for specific data sources that are very unstructured. The effectiveness of Mongo on schema-less data makes it a great tool for us because accomplishing the same things we do in Mongo in MySQL would take longer and be far less performant.
- Very easy to learn and use. Arguably a simpler query language than traditional SQL.
- Large community and excellent documentation. This means many resources and support available.
- Great for dealing with unstructured data. No need to spend time creating schemas (when unnecessary).
- Cost efficient. Free for many types of use.
- Less flexible than traditional SQL (i.e.: no joins). This means it's not suitable for certain data needs.
- Can take up more space than typical relational DB, which can be problematic for very large data warehouses.
- Not fully transactional (ACID compliant).
May 20, 2019
We use MongoDB in one of our major user facing applications designed to showcase the results and analysis of students' assessments. This portal is very complex and contains various views of similar data across different dimensions. MongoDB is used as the underlying DB to help us store and retrieve the myriad data ingested via different sources for our B2B reporting. It addresses one of the major issues of non-relational, async, hierarchical data structure of our streaming data source.
We also use it for few of our other business facing apps as well. They are all independent custom built apps using different front-end technologies.
We also use it for few of our other business facing apps as well. They are all independent custom built apps using different front-end technologies.
- Extremely fast reads and writes if using the right indexes
- Built-in aggregation function for on-demand computations
- Ability to use any cloud provider for implementation. Even their own Atlas service is pretty good and affordable.
- If installing it on-prep or on your own account in a public cloud, it can be a daunting experience.
- Their aggregation functions still have room for improvement.
- Native operational reporting functionality is a bit quirky and you have to pay for it separately. This should come built in and free.
April 09, 2019
At my previous company, we had a mix of SQL and NoSQL databases powering our web platform. When building my new company, we made the decision early to go with a primarily NoSQL database solution. MongoDB powers our web platform, internal tools, and anything else we create. Working with MongoDB is painless and our developers love it - particularly Javascript developers, of which we have many, as we use a lot of Node.js. MongoDB makes development easy and production reliable.
- Ease of use and familiarity, particularly for Javascript developers
- Community, support, and tooling are readily available
- Design with NoSQL in mind and you'll wonder why you ever needed relational features
- Great query language
- Complex querying. Aggregation could be better explained and a bit clearer
March 06, 2019
MongoDB is a solution for our company's NoSQL database. It is currently used by a few departments in our company. Our company needs to store millions of records and needs them to be written and read fairly quickly and MongoDB came into our sight as we looked for solutions. So far we have deployed one cluster and it processes millions of records every day.
- Durability. MongoDB has a cluster structure ensures that data will endure without losing it. The primary-secondary-secondary structure is the key to preserve data.
- Fast response. MongoDB responds to request in milliseconds which is very fast for data processing.
- Price is fair. For the amount of money we spent, the product serves us well.
- I understand the P-S-S structure is meant to be secure but sometimes I feel in some places it is redundant.
- For more complex queries, it can be hard to work with.
- The document is kind of not up to date.
February 28, 2019
Mongo DB is an incredible storage software with a huge database designed for Powerful, easy and intuitive documents. We are using Mongo DB in our team for the Messaging system. Being the Messaging system, it has to find subscribers and send them messages fast. The best thing is to have software that allows you a better development in your area of work. Mongo DB offers the best tool to carry out all our goals.
- As Mongo DB is free for commercial use, it helps in creating the startup from scratch and hit the ground running.
- It makes messaging system management easy on cloud. Mongo DB helps to manage db on cloud.
- Mongo DB should return valid error while using JSON schema. It is confusing if error is not shown properly.
- Support for MongoDB should be improved.
MongoDB is a NoSQL backend storage database that we use extensively for modeling non-relational data. NoSQL databases tend to shine when defined schemas do not well suit a data set — perhaps the dataset is highly variable in the data that it holds from one entity to another, or perhaps the data's structure is simply not well understood. NoSQL and MongoDB are great for this situation.
- Simplifies modeling complex, non-relational datasets.
- Strong open source community.
- Has solid libraries in a variety of implementation frameworks — e.g. Node JS and Mongoose.
- Documentation is at times overly difficult to understand.
- Versioning became confusing between major versions 3 and 4, with many still working on and implementing 4.
- Lacks some of the nice-to-have features of more mature, generally relational databases like MySQL or PostgreSQL.
February 23, 2019
My company is a non-profit healthcare delivery institute, and has been conducting a number of data science/advanced analytics projects collaboratively with other healthcare and research organizations. We had an experience with using MongoDB for a recent big data project with a university that stores genomic sequencing data in a non-SQL database, and developed a web-based visualization tool presenting phenotype patterns based on the data.
- It is basically a well known and popularly used non-SQL database. It provides great performance, especially when reading big sized document or text (such as sequencing), well-developed functions, and online support.
- There are many database developers who are already familiar with MongoDB, like other major non-SQL products. It is easy to hire engineers with reasonable payment.
- Since our project was genomics research, we handled tables with numerous rows and large file size. MongoDB was performing well in hard conditions and very stable.
- There is no JOIN and TRANSACTION, so it was required to add those by application developers. It was mandatory for us to do it since we had to merge genomics data in MongoDB with RDBS based clinical data.
- MongoDB doesn't provide good data wrangling functionalities, such as parsing JSON or XML.
- Data type definition in MongoDB is somewhat different than other databases, and results in some learning curves for our DB and app developers.
February 14, 2019
The software has the facility to balance loads which allow [for] better storage of files and no need to pay for the license. It is a completely free of cost software; it contains high security.
- 3rd-party libraries and framework support are increasing day by day.
- We get too many tutorials for understanding MongoDB. Provide a proper tutorial which is easier for a developer to understand the code.
- Adding more and more features will motivate the developer to use MongoDB.
- Third party library should be increased.
December 19, 2018
We have been able to take advantage of this tool since being a non-relational database, it is much easier to build the model of the architecture of the database model. This makes the development time much easier. When working with javascript language, or working with JSON objects and collections, MongoDB makes the connection of services for queries much lighter and optimizes the performance of the applications. Also, you can work, in case you do not know the console commands, with a Desktop database administrator in a graphical way. The learning times really are much faster, which allows a great scalability of the project. In the development department, this optimizes the delivery time with the clients, which makes the projects much more feasible in terms of delivery times.
- 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.
- MongoDB seems to be one of the most complete tools in its field, I believe that it has all the features that a non-relational database should have.
- Perhaps because it is a relatively new tool there are very few experts in the field of MongoDB.
I have used MongoDB as the database of choice for a NoSQL implementation for various apps. Implantation with Node.JS and Express is very seamless and easy, particularly when using Mongoose. Dealing with a document based solution for a database makes it pretty easy to use in a full stack Javascript app without needing to flip mindsets.
- Easy to run locally on a dev machine
- Easy to integrate into a schema model via Mongoose
- Document-based storage makes it easy to work within a full stack Javascript environment
- Getting MongoDB installed locally can be a challenge
- The CLI can be kind of confusing for beginners, but MongoDB Compass makes up for that
December 14, 2018
We use MongoDB in the company's software development department to storage a large set of data for a meteorological forecast application. The data were provided by a third party service and refreshed every 5 minutes. Mongo was chosen to manage all the data. It's also used for a service of dynamic forms developed in the company.
- With the ideal performance configuration, MongoDB is a great tool to manage data in a blazing fast way.
- The document-oriented database has certain advantages: good fit for modern JavaScript frameworks (direct use of JSON), flexibility, big data processing and real time statistics/data analysis.
- MongoDB is very easy to understand.
- The resulting database is heavier than in a SQL relational database system
MongoDB Scorecard Summary
Feature Scorecard Summary
What is MongoDB?
MongoDB (from "humongous") is an open source document-oriented database system developed and supported by 10gen. 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.
According to the vendor, organizations from cutting-edge startups to the largest companies use MongoDB to create applications never before possible at a fraction of the cost of legacy databases. The vendor says MongoDB is the fastest-growing database ecosystem, with over 10 million downloads, thousands of customers, and over 1,000 technology and service partners.
According to the vendor, organizations from cutting-edge startups to the largest companies use MongoDB to create applications never before possible at a fraction of the cost of legacy databases. The vendor says MongoDB is the fastest-growing database ecosystem, with over 10 million downloads, thousands of customers, and over 1,000 technology and service partners.
MongoDB Screenshots
MongoDB Video
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MongoDB Integrations
MongoDB Competitors
Couchbase, Apache Cassandra, Oracle Database (legacy)
MongoDB Pricing
- Has featureFree Trial Available?Yes
- Has featureFree or Freemium Version Available?Yes
- Does not have featurePremium Consulting/Integration Services Available?No
- Entry-level set up fee?No
MongoDB Technical Details
| Deployment Types: | SaaS |
|---|---|
| Operating Systems: | Unspecified |
| Mobile Application: | No |