TrustRadius Insights
MongoDB has emerged as a popular choice for developers and organizations seeking a fast and efficient NoSQL data layer for their web …
Starting at $0.10 million reads
View PricingOverview
What is MongoDB?
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…
Recent Reviews
Awards
Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards
Popular Features
- Availability (38)9.797%
- Performance (38)9.090%
- Concurrency (38)8.686%
- Security (38)8.686%
Pricing
Shared
$0
Cloud
per month
Serverless
$0.10million reads
Cloud
million reads
Dedicated
$57
Cloud
per month
Entry-level set up fee?
- No setup fee
For the latest information on pricing, visithttps://www.mongodb.com/pricing
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
Starting price (does not include set up fee)
- $0.10 million reads
Product Demos
MongoDB Change Streams: The Hidden Gem within the MongoDB Repertoire
YouTube
MongoDB & Tableau FAA Demo
YouTube
NoSQLMap MongoDB Management Attack Demo
YouTube
Intro to MongoDB with C# - Learn what NoSQL is, why it is different than SQL and how to use it in C#
YouTube
MongoDB with Python Crash Course - Tutorial for Beginners
YouTube
Features
Return to navigation
Product Details
- About
- Integrations
- Competitors
- Tech Details
- FAQs
What is MongoDB?
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.
MongoDB's flagship Enterprise Advanced edition is a collection of products and services that drive security, efficiency, to put users in control of MongoDB Databases. These include:
MongoDB is available as a managed cloud solution via MongoDB Atlas. But MongoDB Enterprise Advanced offers advanced access control and data security features to protect on-premise or private cloud databases, and satisfy compliance or customer requirements. It’s also designed to make it easy to integrate MongoDB with any existing security infrastructure and tooling.
Organizations from startups to the largest companies can use MongoDB's capabilities to create applications never before possible at a fraction of the cost of some legacy databases. The MongoDB database ecosystem boasts over 10 million downloads, thousands of customers, and over 1,000 technology and service partners.
Also, the MongoDB Community Edition is licensed under what the company provides as the Server Side Public License (SSPL), which is based on the GPL v3. All MongoDB Community Server patch releases and versions released on or after October 16, 2018, will be subject to this new license, including future patch releases of older versions. The Community version of the distributed database offers a document data model along with support for ad-hoc queries, secondary indexing , and real-time aggregations to provide ways to access and analyze data.
MongoDB's flagship Enterprise Advanced edition is a collection of products and services that drive security, efficiency, to put users in control of MongoDB Databases. These include:
- MongoDB Enterprise Server - the commercial edition of MongoDB, which includes additional capabilities such as in-memory storage engine for high throughput and low latency, advanced security features like LDAP and Kerberos access controls, and encryption for data at rest. Enterprise Server is included with the MongoDB Enterprise Advanced subscription, which includes expert assistance and tools. Or, the MongoDB Enterprise Server is also available free of charge for evaluation and development purposes.
- MongoDB Ops Manager - Tools for managing MongoDB in a secure, on-premise or owned environment. Available through the MongoDB Enterprise Advanced subscription, Ops Manager eliminates operational overhead by automating key administration tasks such as deployment, and upgrades. Tools also support monitoring with visualization of performance metrics, continuous or point-in-time incremental backup, and query optimization with the Visual Query Profiler.
- MongoDB Enterprise Kubernetes Operator - Kubernetes Operators are application-specific controllers that extend the Kubernetes API to create, configure, and manage instances of stateful applications such as databases. On self-managed infrastructure – whether on-premises or in the cloud – Kubernetes users can use the MongoDB Enterprise Operator for Kubernetes and MongoDB Ops Manager or Cloud Manager to automate and manage MongoDB clusters.
MongoDB is available as a managed cloud solution via MongoDB Atlas. But MongoDB Enterprise Advanced offers advanced access control and data security features to protect on-premise or private cloud databases, and satisfy compliance or customer requirements. It’s also designed to make it easy to integrate MongoDB with any existing security infrastructure and tooling.
Organizations from startups to the largest companies can use MongoDB's capabilities to create applications never before possible at a fraction of the cost of some legacy databases. The MongoDB database ecosystem boasts over 10 million downloads, thousands of customers, and over 1,000 technology and service partners.
Also, the MongoDB Community Edition is licensed under what the company provides as the Server Side Public License (SSPL), which is based on the GPL v3. All MongoDB Community Server patch releases and versions released on or after October 16, 2018, will be subject to this new license, including future patch releases of older versions. The Community version of the distributed database offers a document data model along with support for ad-hoc queries, secondary indexing , and real-time aggregations to provide ways to access and analyze data.
MongoDB Features
- Supported: Comprehensive monitoring for full-performance visibility
- Supported: Automated database management for 10-20x more efficient ops
- Supported: Fully-managed backup for peace of mind
MongoDB Screenshots
MongoDB Video
What's New in MongoDB 7.0 Explained in 3 minutes
MongoDB Integrations
MongoDB Competitors
MongoDB Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
Frequently Asked Questions
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.
MongoDB starts at $0.1.
Reviewers rate Availability highest, with a score of 9.7.
The most common users of MongoDB are from Enterprises (1,001+ employees).
Comparisons
Compare with
Reviews and Ratings
(431)
Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
- Recommendations
MongoDB has emerged as a popular choice for developers and organizations seeking a fast and efficient NoSQL data layer for their web applications. Its flexibility and iterative development capabilities have made it invaluable in various use cases. For example, MongoDB is being utilized by engineering departments to power SaaS platforms, allowing clients to create and configure assets for account-based marketing efforts. The document store of MongoDB proves ideal for handling complex configurations with nested structures. Additionally, the native JSON support is convenient and valuable when working with data needed in web browsers. MongoDB's aggregation framework enables the generation of complex reports and dashboard reports, which are immensely beneficial for businesses. The replication feature of MongoDB seamlessly allows applications to scale and support numerous clients, further enhancing its utility.
Furthermore, MongoDB has proven its worth as a temporary mid-size storage database for processing massive amounts of data per day and extracting notable events and records for further analysis. It facilitates quick application development in the cloud, enabling free usage and evaluation of system loads. Additionally, MongoDB serves as an internal database type in REST APIs for high-load applications. Compared to traditional SQL systems, MongoDB stands out due to its scalability and superior performance in terms of reads and writes. Its simplicity and clarity make it a preferred choice when dealing with large amounts of data. Furthermore, MongoDB is extensively used as the main storage technology for web development projects employing the MEAN Stack. Its scalability and unstructured document storage are particularly valued from a business perspective.
Moreover, MongoDB's non-relational nature simplifies database modeling and optimizes performance when working with JavaScript or JSON objects. It has been recognized for optimizing delivery time, making projects more feasible within specified timelines. MongoDB is widely employed as the main persistent datastore for SaaS offerings, providing robust and scalable solutions. It finds immense utility in large-scale, high-transaction environments as well by storing analytics information from social networking sites or serving as the primary datastore for Intranets. Additionally, MongoDB handles data with hundreds of variances effectively, which can be challenging to manage in a relational database. Its lightweight alternative for front-end-heavy projects and document-based data storage makes it a compelling choice over traditional RDBMS solutions. Consequently, MongoDB proves useful for managing a large amount of information, making it a preferred choice for banks and large institutions.
Moreover, MongoDB's application extends to various domains such as train yard management applications, where it enables easy management of JSON structures within a database. Gradually, MongoDB is being adopted by different teams and products after resolving scaling and sharding issues. It is highly regarded by software development teams for its efficiency, easy learning curve, and efficient query languages. MongoDB bridges the gap between data analysis and developers by facilitating the structuring of databases and primary querying. Consequently, organizations across industries utilize MongoDB for developing internal applications as well as apps for other companies.
MongoDB's robustness and scalability make it suitable for handling millions of unstructured records, such as defect management in software projects. It excels at building multiple dashboards and metrics from data using simple find queries, aggregation, and MapReduce operations. MongoDB also serves as a reliable storage solution for handling intense database use cases, storing critical customer information, rules, configuration data, and content for alert notifications and statements.
The horizontal scale-out capabilities of MongoDB coupled with its ability to work with complex structures of information make it a chosen technology for many applications. Its ease of use during the initial stages of a project and its ability to handle data increase quickly are additional reasons why programmers favor MongoDB. It is commonly used as a store of user accounts and app settings for mobile apps implemented in JavaScript and Node.js.
Furthermore, MongoDB helps improve response times by scaling systems horizontally and distributing the load effectively. It supports agile methodology software development life cycles with its dynamic schemas, which facilitate iterative development and rapid prototyping. Developers appreciate MongoDB as an efficient NoSQL database that offers scalability coupled with good support and helpful documentation.
Additionally, MongoDB solves performance problems in APIs by providing an easy-to-scale solution while enabling developers to work in an agile manner and improve response time. Its ability to store non-relational data like user profiles and application logs makes it a popular choice among developers who need to work with diverse datasets. Moreover, MongoDB enables fast prototyping of new APIs by saving time wasted on data conversion.
MongoDB's versatility extends to various programming languages and operating systems without posing any challenges. It has gained significant traction in the academic community, with students utilizing MongoDB extensively in software engineering projects. It serves as a valuable tool in testing environments, helping students understand popular NoSQL databases and preparing them for development positions.
Furthermore, MongoDB is the preferred choice for managing transactional databases in gaming, offering features like replica sets, sharding, and clusters. Its flexibility and quick prototyping capabilities make it the main database for SaaS products, allowing for the easy exploration of new product ideas.
In a web application context, MongoDB acts as a comprehensive storage solution, hosting all necessary data including user details, application configuration, and user-managed data. It serves as an internal database type for organizations, handling millions of records across multiple departments.
MongoDB's capabilities extend beyond traditional web applications. It plays a crucial role in messaging systems, allowing for fast subscriber finding and efficient message sending. Its ability to model non-relational data when defined schemas do not suit the dataset makes it extensively used in various business-facing applications built with different front-end technologies.
Additionally, MongoDB powers web platforms, internal tools, and other applications as a primarily NoSQL database solution. It is leveraged by multiple departments within companies to store and process large volumes of records. MongoDB's versatility also shines in managing complex portals that showcase student assessments and support B2B reporting.
Moreover, MongoDB serves as a reliable datastore for extensive big data associated with users in an application. Compared to SQL Server, MongoDB provides a better platform for big data storage and analysis. Its capabilities are harnessed by storing and retrieving data for complex portals, enabling effective B2B reporting.
In conclusion, MongoDB has proven its worth across a wide range of use cases. From empowering SaaS platforms and handling complex configurations to supporting dashboard reports and scaling applications to serve numerous clients, MongoDB offers flexibility and efficiency in managing data. Its performance advantages over traditional SQL systems, scalability features, compatibility with JavaScript and JSON objects, ease of use for developers, and extensive documentation contribute to its widespread adoption across industries. Whether it's powering web development projects or managing transactional databases for gaming, MongoDB continues to be an instrumental tool in modern software development and data management.
Based on user reviews, the most common recommendations for MongoDB are as follows: Consider MongoDB for specific use cases such as applications where delays are acceptable or rapid prototyping and automatic shredding of data. It is also suggested for full-stack web development with JavaScript and implementing JSON-style database storage.
Evaluate data needs and scalability by analyzing data requirements before deciding to use MongoDB, especially if the data is relational. Consider MongoDB's ability to store large amounts of data and apply sharding mechanisms for scalability.
Seek professional help and resources during the early stages of MongoDB adoption. Stay in touch with MongoDB professionals in enterprise environments. Utilize resources like MongoDB University for learning purposes, proper documentation, and online guides for installation. Additionally, test MongoDB before implementation and benchmark against other databases for comparison.
It's important to note that these recommendations are based on user opinions and their applicability should be evaluated based on individual requirements and circumstances.
Attribute Ratings
Reviews
(1-25 of 31)Companies can't remove reviews or game the system. Here's why
July 26, 2022
Why is MongoDB good
Due to the software developments made, the institution's NoSQL technology was needed. Therefore, a solution was created by purchasing the enterprise version.
- We preferred the application because it stores documents in a JSON-like format. No need for extra format conversion.
- Allows changes to the structure of documents and stores partially completed documents. The recorded data can be read very easily.
- Can be user friendly. While it is very easy to create indexes in other database applications, it is a bit cumbersome to do this in Mongo.
- The difficulties that we do not encounter when working with much larger data on MS SQL make us very difficult when working with fewer data in mongo due to the in-memory feature.
- Since MSSQL does not have the unlock feature, it causes writing conflicts while reading and writing data at the same time.
July 06, 2022
Perfect No SQL DB is here
Quick application development in the cloud in a no-SQL environment. For POC purposes, we sometimes are able to get free usage and also can evaluate the loads on the system which can be exploited to estimate real-time loads.
- Storage of dynamic data from any source
- Data agnostic
- JSON-formatted data query
- Max limit on document storage
- No cross table joins
- the backend architecture is complex and requires good understanding before developing the queries
January 17, 2022
Oleg's MongoDB review
Score 10 out of 10
Vetted Review
Verified User
We use it as one of the internal database types in our REST APIs via a Spring/JAP connection in high-load applications. MongoDB is highly scalable, and compared to traditional SQL systems, reads and writes much faster than SQL. What is done on Mongo is as simple and clear as possible, and if there are problems with the amount of data in relational databases, such “bicycles” will have to be invented that will reduce all the advantages of these databases to zero. It’s probably hard to do an initially limited project on ordinary relational databases, that is, not to think about what will happen when everything is slowly covered up ... It’s better to devote more time to the design of the initial data, which will remove all questions in the future.
- MongoDB is highly scalable.
- Reads and writes much faster than SQL.
- What is done on Mongo is as simple and clear as possible.
- Requirement from the application in a highly scalable database.
July 26, 2021
Want to gain insights from unstructured data? This is the tool that everyone should use.
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.
Currently I am using it for storing and analyzing the live stream data. This works very fast and can be used by creating our own personal data types. We are taking huge volume of data for storage and processing made is very easy. Just connect and analyze it's that easy.
Currently I am using it for storing and analyzing the live stream data. This works very fast and can be used by creating our own personal data types. We are taking huge volume of data for storage and processing made is very easy. Just connect and analyze it's that easy.
- Reads real-time data very accurately and fast.
- Syntax are so easy to learn and understand
- Connection with the other tools through API's is also pretty simple.
- Storing any type of data by creating personal data types.
- Live streaming data processing is very fast.
- Some basic statistical functions are there but we can apply high analytics models 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. Depends on the cloud source as well.
- Sometimes it stucks, if columns are defined enough and data has some missing info as unstructured data can be of any type.
- Sometimes very difficult to apply functions on the data types for that huge research is required.
May 21, 2021
Stable & Easy to Use
MongoDB was our first NoSQL database usage. For this reason, we assigned it to an application that serves inside our IT infrastructure. As a result of our approximately 3-4 years of experience, we did not encounter any problems. It writes the data sent on it without any intervention and without any interruption, every second without stopping.
- Flexible
- Fast and easy to use
- Open source
- Free
- İndexing is easy
- No joins
- Administrator GUI
- Documentation can be more useful
- Not ACID Compliant
May 08, 2021
No relation, no worry
Used as a database solution for a web application for storing all data needed. That means all user details, application configuration and data created or managed by application's users is stored in MongoDB. It's used both by software developers for implementation purposes and also by support crew who maintain the application.
- Simple structure, easy to understand how it works.
- Easy to integrate with cloud providers.
- Writing queries is easy to get started with.
- When more complex queries are needed, they are more difficult to write than SQL equivalents.
- Getting used to the aggregation framework takes some effort.
- Upgrading between versions has required some additional work from developers in the past.
April 19, 2020
MongoDB: King of NoSQL
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
MongoDB, for big unstructured data, it just works.
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.
December 12, 2019
MongoDB is the best NoSQL DB
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.
May 20, 2019
MongoDB - Best DocumentDB out there !
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.
March 06, 2019
One of the best NoSQL databases you can get
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
MongoDB is best tool for NoSQL type based database
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.
February 28, 2019
One of the best NoSQL family databases
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 23, 2019
MongoDB is a safe choice for genomics research project
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.
December 11, 2018
Developer perspective on MongoDB
For a few years now our company has been replacing some very expensive Oracle DB's with much less expensive and lightweight combination of MongoDB with Elastic Search assisted collections. We have some extremely data heavy collections that used to take upwards of 30 seconds to search. With only Mongo collections and not having a normalized database I think we would have seen improvements, however, using Mongo in conjunction with Elastic has allowed us to make similar and more complex queries in fractions of a second.
- Easy to set up in AWS.
- Easy to scale. If you're worried about growth while maintaining consistent performance adding nodes is easy.
- Mongo typically will typically require more storage space for the "same" amount of data stored in a normalized database.
- Many features of other popular databases aren't available in Mongo such as Joins and Transactions.
MongoDB using to store all clients info and their invoices and settlement info. This also used to keep a record of customers queries and frequently asked questions by customers.
- The schema-less feature really makes it easier to use.
- As we know this is free and it allows to run queries on Linux as well.
- Data retrieving is faster than other databases.
- It provides less flexibilty while writing complex queries.
- It should support multiple document level.
- This takes higher size to store data.
February 13, 2018
If you want easy management and creation of database, MongoDB should be your choice
I work in the informatics department. We currently manage the databases of some banks in my country and the employees of the IBM branch in Venezuela. I believe that it facilitates the management of a large amount of information, which is why bank branches choose us as their operators.
- Unlike relational databases, NoSQL databases are based on key-value pairs. MongoDB is the major NoSQL database.
- Some types of NoSQL database stores include column stores, document stores, key values, graphics, objects, XML, and other data warehouse modes.
- The interface is a little complicated to learn.
- They could improve compatibility with other NoSQL databases.
- I have had problems with data relationships when information is very large.
October 06, 2017
I'm Liking What I'm Learning
Score 9 out of 10
Vetted Review
Verified User
MongoDB is being used as a free-flowing document store for tax information.
- Allows for free-flowing attributes
- Scales easily
- Improving with each release
- Re-sharding can be cumbersome
September 21, 2017
Awesome Product
It's an awesome product. I started work with it 10 months ago. It is a very original, flexible, and attractive product.
It is a document database in which one collection holds different documents. The number of fields, and content and size of the documents can differ from one document to another.
It is a document database in which one collection holds different documents. The number of fields, and content and size of the documents can differ from one document to another.
- It is schema-less
- Faster turnaround in development
- MongoDB has the best features of key/ value stores, document databases and relational databases in one
- Trigger function
- Max BSON document size is 16MB
- Mongo provides GridFS to get around this , No more than 100 levels of nesting
September 12, 2017
MongoDB - the game changer
Score 9 out of 10
Vetted Review
Verified User
As a consultant I am working on our latest project as Solution Engineer and Dev Team Lead. MongoDB is used to save configuration data of any kind of device used in the scope of the company (a kind of CMDB). This data is structured by device, so in best case we can talk about semi structured data for a database perspective. To handle this it needs a flexible schema or a base set of relational tables surrounded be exception tables. Both would work to save the data. But when it comes to make use of it, the flexible schema of MongoDB pays dividends. Queries are much faster, and any adoption of a new device can be done with almost no impact, whereas we would need to define a further exception in the relational model.
Also the development turned out to be leaner since we could simplify the queries, and API.
Also the development turned out to be leaner since we could simplify the queries, and API.
- Replication is a real plus; it is shipped out of the box and a simple three-node replication set can be setup with a few commands in less than 5 minutes.
- Sharding steps in the same direction as replication, just more complex - what is in the nature of the issue since we are talking about distributed databases.
- MonogDB is light and easy to run and administer
- Monitoring is still a little bit difficult, though the latest releases of Compass (MongoDBs Monitoring tool) have led it to catch up.
August 31, 2017
MongoExp
Score 9 out of 10
Vetted Review
Verified User
Currently, we use MongoDB for handling defect management for our company. There are several millions of unstructured records that come into the system and are queried by users. MongoDB handles these things smoothly. We build multiple dashboards and other metrics from MongoDB data, these are performed using simple find queries, aggregation, and MapReduce, they do the job seamlessly and smoothly.
- Indexing
- Sharding
- Replication
- Monitoring of Mongo infrastructure
August 02, 2017
MongoDB for multiple purposes
Score 9 out of 10
Vetted Review
Verified User
I'm in charge of the database of the global department that sends all the alert notifications and statements for customers and we have a really intense use of the database. We store some customer information, rules and configuration for each product and country, and some of the content we send. We chose mongodb because of the horizontal scale out and the ability to work with complex structures of information.
- Index creation: you can perform the process in rolling fashion, one server at a time avoiding performance issues or outages. In fact, a lot of maintenance task could do it this way.
- Changing of the schema, we just deployed the new version of our new application, don't need to touch the database (in most cases).
- Compression: the new storage engine (Wired Tiger) supports compression in a faster way.
- JSON, once you know how to use it, it's a really good way to work with the database, I like it more than SQL, and it's really friendly with javascript, and node.js.
- Well, I found some little differences between the behavior of mongodb and the documentation, (not related with a different version of the server)
May 11, 2017
Wearable device development with MongoDB
MongoDB is used to store data for electric measurement (of an original product, a wearable device called puck for brain stimulation) as well to get users' feedback after usage. Our day-to-day work relies on MongoDB solely. You might be asking that's why did we use MongoDB at first instance! Well we were never sure of the volume of data that we will be dealing with. The amount of data we process right now is still very small(gigabyte only). But the story doesn't end here. We have an active replica set for our production. If the story makes a success we will be needed to create sharded cluster very soon. Hope so for now. As it happens now if we want to rewrite the whole code base we will be in a soup, MongoDB is so deeply integrated with all of our framework. Its the lifeline for our product and project.
- Roll out new features in a timely manner: As we evolved from an experiment to a publicly available product, we saw MongoDB evolved with the same pace. Right now you can work with MongoDB with ease. Some people think it will take a huge amount of time to develop an application with MongoDB. But I can tell you the community has been growing and thriving. No need to get scared by relational databases anymore.
- Strong support team: We had active support from MongoDB. I feel that was great. As I never had a ridiculous answer from the support team. They were always prompt, sharp and will have exact reasoning for the problem. The feature I like the most is virtually every language is supported by MongoDB for application development. Which made our job easier as a few developers and QAs were not accustomed to MongoDB.
- New integration and frontiers: I feel the journey just started. With the Spark integration, MongoDB opens a new door for analytics which is great. We need more such features for analytics.
- Reliability and durability: I replaced an existing replica set by a new one within few hours including data transfer. I don't know how fast it is for a relational database. I've never found any write or read failure of our production database. My application transfers data into megabytes to a mobile device within a few milliseconds, which is quite amazing.
- Security and endured performance: With all our performance test results we are quite satisfied. The security is enhanced with https based communication among the replica set nodes. Even here you have user level access like a relational database but data can be grown much more than a relational database. With MongoDB, the performance we got was phenomenal and helped us to remove usage of the caching server.
- Analytic: This area needs quite an overhaul with new features and integration. I think it has to be more thoughtful.
- Migration: Needs hassle free migration from one version to the next or the previous. As of now, this feature is getting huge attention. Hope [they] will do better in future.
- Query functions: Like RDBMS SQL functions are missing. Need to use aggregation framework for simple calculation, which is time taken and slow to run. Hope new functions will be added with new improvements.
- Community driven features: Add more community driven features so that developers can write less code and do more.
January 03, 2017
Accelerate delivery with this general purpose NoSQL engine
Score 9 out of 10
Vetted Review
Verified User
MongoDB is used across the whole organization in several use cases. There are use cases which are utilizing the technology, for high-throughput, or high data volume on a level which may not be economical with different technologies, and there are others, which only would like to leverage the fast development cycle made possible by the dynamic-schema design.
- High data volume low latency access.
- Rich indexing and querying capabilities
- Enterprise grade tooling. (Ops Manager, advanced Security)
- There is no cross-cluster replication of any kind. That would be very useful in many cases, like disaster recovery or test data delivery to pre-production validation.
- There is no multi-document transaction capability. This could be accepted with limitations like a transaction only on 1 shard.
- Most of the tooling is closed source, and tends to be a bit buggy.
June 03, 2016
MongoDB - a beginners review
MongoDB was used to store middleware transaction messages. These JSON messages were sent across various heterogeneous systems like Maximo and Click Sycleo etc. It was only used to store the important messages for local use and references. The main system software IBM Maximo used a relational database. MongoDB was locally set up to store templates of frequent and different types of middleware messages.
- Since Mongo DB stores unstructured data, it was easy to directly store messages in it. We did not have to de-serialize serialize the json data
- Of bulk messages where exported from the Oracle Service bus which was the middleware into csv. The import of all the messages from the CSV and MongoDB was done using a single command
- Complex queries can get confusing at times when comparing multiple constraints. The query language needs a bit of improvement.
- Joins like mechanisms are missing in MongoDB.