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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…
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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
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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).
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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.
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July 24, 2022
MongoDB - A Stellar NoSQL Database
In my organization, we use MongoDB as a temporary mid-size storage database. We have very large databases and process a massive amount of data per day. Throughout the day we identify notable events and records and need to extract them for continued analysis. This is where our MongoDB environment comes into play. We roll all of these detected records into MongoDB for further use.
- Very simple with easy to learn and understand syntax.
- Offers great flexibility as their is no predetermined schema.
- Scalable - handles all our our data very effectively even as we scale up.
- Data duplication can be a problem - have to make a concerted effort to avoid this.
- Memory usage can be an issue depending on infrastructure.
- Certain commands that may work well in something like MySQL may not in MongoDB, such as join commands.
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
June 11, 2021
MongoDB by a front-end guy
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.
May 24, 2021
No data relations, go MongoDB!
MongoDB is one of the main databases we use for our SaaS product. Its flexibility and ease to develop with allows our development team to quickly prototype and validate new product ideas, allowing us to bring new features to the market at a much faster speed.
- Scaling and replication.
- Easy to develop with.
- Good support by many cloud vendors.
- Good tool support, such as MongoDB Compass.
- Query becomes more complex when your data starts to have relations.
- The aggregation framework has a bit of learning curve.
- Being schema-less can sometimes lead to bad data modeling designs.
- If you need to change the name of an attribute (i.e. column name of a table for SQL), it can become tricky.
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.
May 07, 2021
MongoDB is the way to go!
MongoDB is our primary database our application runs on. We use it intensively for our application development and data warehousing. I have used as a datawarehouse for analytics. It currently gets data from multiple dbs like mysql, app insights logs and other Mongo instances. I primarily use it for everyday metrics and analytics reporting
- Robust and Out of the box DB
- Mongo Compass Integration provides a sweet GUI for users
- Well optimized No SQL DB
- Great Community support
- Sometimes queries are tricky to execute
We use MongoDB as the main storage technology at the backend level for projects related to web development using the MEAN Stack (MongoDB, ExpressJS, AngularJS, NodeJS).
From a business point of view, the best features it provides are scalability and unstructured document storage, which allows us to have a flexible schema for the data.
- Load balancing and data replication
- Indexing and Document validation
- Support for different programming languages and integration with different frameworks
- Good query performance
- Not the best solution for applications with complex transactions and many parallel operations
- It is not an optimal solution if the application needs to update the database frequently.
- Usually requires more disk space
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
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
Fast, easy to use!
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.
August 27, 2019
MongoDB: Scalable NoSQL Database
Score 9 out of 10
Vetted Review
Verified User
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
June 14, 2019
Review for MongoDB software
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.
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.
April 09, 2019
Moved to Mongo and never looked back!
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 14, 2019
MongoDB: easy to use, easy to shot yourself in the foot
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.
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 23, 2019
MongoDB Review
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 22, 2019
MongoDB - Best NoSQL Database to Store Unstructured Data
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).
February 14, 2019
MongoDB is best NoSQL database software for keeing large data.
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 22, 2018
MongoDB: Easy and powerful
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 19, 2018
MongoDB, noSQL, noRelational, noProblem
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.
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.
April 02, 2018
A NoSQL database for even the Non-data expert
We utilize MongoDB for both an internal custom CRM that handles our day to day operations and also in some of our products that are currently in service. We also have some apps in development that are yet to launch which use it. MongoDB is a fast and efficient NoSQL data layer for our web apps that allows us to be flexible and iterative with our development.
- Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
- Fast performance.
- It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
- There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
- Query syntax is pretty simple to grasp and utilize.
- Aggregate functions are powerful.
- Scaling options.
- Documentation is quite good and versioned for each release.
- 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.
February 09, 2018
It is open-source, cross-platform and schema-less.
Yeah, I liked this MongoDB advanced version of SQL we solved many businesses problems with MongoDB. It stores huge amounts of data used by our organization to store market customers databases on our server.
- Its ease of scale means auto balancing and reads by using replica sets.
- It's cheaper in cost and depends upon RDBMS structure. It is platform independent and we can run on Linux as well
- Its DB is schema-less if you want free and flexible table documents you should follow MongoDB so I recommend it
- When one problem occurs we can't use joins and flexibility queries.
- Data size in MongoDB is typically higher due to document failed names stored it.
- It is not a great solution for performing a lot of writes when data size grows. It became lazy and we use other software to bring it back.