Fast, fast, fast, and agile
Very positive. I will likely use MongoDB on every future project of moderate to extreme complexity.
One of the most difficult parts of software development, especially with complex projects, is keeping the software maintained. As business requirement change, the effort required to make those changes grows over time. MongoDB opened up a whole new world for me. I can make structural changes to my underlying data with ease without too much modification the data access layer. It reduces initial development significantly, and allows my team to pivot to new requirements with unprecedented ease. Because related data is encapsulated, queries are much faster, and our software is extremely performant. Highly recommended.
The tooling isn't great. Compass is a decent tool for accessing and lookup, but it lacks polish. It's slow to start up and sometimes difficult to pull up the data I'm seeking
One of the best for Web Developers
Unlike SQL, it has no joins, which can sometime be an issue in some data retrieval cases. Sometimes it works very slow in the cloud environment. There are no functions available for Transaction. MongoDB's documentation is much confusing to the users. Even if it's easy to use and learn, learning MongoDB might take some time. I thinkg it is hard to work with complex queries.
Mongo allows you to take off easily, but makes it harder to do more advanced analysis.
-Getting simple data in/out is painless & straightforward
-Basic analytics are easy, as is managing multi-server clusters
-Working with complex data is a difficult.
-Many original features or design choices were incorrect and slow to be corrected. For example, timezone support is minimal and days/dates/months use a custom numbering rather than ISO. Mongo is only now adding ISO versions of aggregation commands
Great data storage solution with space for improvement
Using MongoDB for years, mostly as local storage in docker containers. Latest project is based on cloud solution.
I like the Atlas Cloud solution. It enables various tricks and cross-integrations of single database between multiple apps (containers) with simple user management - for a reasonable price.
I cannot get over this Atlas Compass UX issue - I want to open at least two "tabs" with collections at the same time. This is not possible and even worse, when you switch between collections, thee state is completely reset.
So I'm compiling the search query carefully with all the commas, brackets and identifiers, I often need to search for ID from another collection or maybe from the same collection. When i change collection scope -> BAM! The whole query is gone :( The input should retain its actual value...
Second "issue": When it comes to schema changes in living DB, sometimes it behaves unexpectedly (no error, no data). Maybe I'm doing something wrong, but I would like to know it...
Fastest leap In database management
I use mongo with our applications. For any set of data, this is the best database.
Really speedy and requires less memory.
We can create collections without a definite number of rows and columns to come.
We can add data without restrictions
It gives a JSON output which is really easy to work with
Easy to add , edit and remove data
If a certain section has more than one data, we can insert them as sub arrays, and it makes the developments so flexible.
The free version allows limited memory so that we have to upgrade it to insert unlimited data. Other than that this is the best.
Stellar DB solution—Easy to learn!
MongoDB has been the perfect solution for the MillerEC. I've loved learning to use it and look forward to deploying projects with it in the future.
- incredibly easy to learn and integrate into code
- fantastic support and built out systems for different languages (Nodejs, for example)
- the free version is all I have ever needed. It rocks
- it lives on its on servers. That's usually great, but makes testing difficult at times and does not feel as proprietary as one's own SQL servers
MongoDB Management Experience
Easy to use, deploy, and configure
MongoDB is very stable and reliable, easy to scale if needed. Its deployment is just a click away.
If you're looking for a NoSQL DB, MongoDB is a viable option.
MongoDB is free, performs really well, and it is easy to deploy and configure. There is a big support community, but the documentation is most of the time enough.
No issues so far. It was easy to deploy a couple of clicks and that is it. Even to configure access control, replication, and whatnot can be easily found in their documentation or on the internet.
Go-to Non Relational DB
Decent alternative to SQL database. Works super well if your model doesn't depend heavily on relations.
- Easy to use and get started with
- Good documentation of the API
- Official client libraries exist for popular programming languages
- Large community and availability of tutorials to get up to speed
- Doesn't work so well once you start having relationships in your model
- The aggregation framework could be better
- The free text search could also be better
Amazing database storage system
MongoDB gives plenty of flexibility thanks to the use of documents that can handle unstructured data (non-strict schema). MongoDB simplifies the way that data is stored and handled.
MongoDB is a good storage system that handles data in a different way than the traditional relational databases. MongoDB is very flexible with the use of documents with a non strict schema instead of the traditional rows and columns system with a predefined schema.
MongoDB is a great database for working with big data and IOT (Internet of Things) related projects with very good performance.
MongoDB is highly scalable when using Sharding (horizontal scaling), distribuiting and accessing data across several servers, instead of scaling up adding more hardware resources.
When developing apps that grow/change constantly in scope and data, you have to handle different methods to support documents with different data structure.
Moving from relational databases to NoSQL databases is hard, because you have to change paradigms in the way that you work with data.
Learning the query language is not as straight forward as in RDBMS.
Amazingly Flexible Database Capability
I don't usually rave about products, but I do about MongoDB.
* MongoDB's schemaless document-centric approach to database makes it easy to store any kind of data I need to, even subdocuments and array fields with minimal fuss within code or tools. This allows for a lot of flexibility and makes it easy to upgrade or refactor existing software.
* MongoDB's indexes provide amazing performance even in a schemaless world. Simple and compound indexes, as found in the relational database world, are just the start. Add to that multikey indexes (indexes over array fields), string and geolocation indexes, and indexes where entries expire documents with time. Mongo has it all.
* MongoDB's approach to scalability - using replica sets for high availability and fault-tolerant failover and sharding databases over a potentially large number of servers - makes it easy to scale huge amounts of data without overly expensive hardware and failover complexity.
* MongoDB driver support is available for a variety of languages.
* Mongo University, free graded courses covering various aspects of MongoDB from development to administrative activities to security, etc., offers a solid path to learning.
I'm a huge proponent of MongoDB but because of the nature of schemaless document-oriented databases, there are still some problems for which a relational database is still the answer. There are some applications and technical domains where relational databases still have a huge lead over Mongo for performance.
MongoDB is the NoSQL leader and getting better
The first decision about whether to use MongoDB or not is whether you need a relational or non-relational DB. Once you decide a non-relational is best for you project, then MongoDB is a solid choice. It has the ongoing support of a professional team and is widely used in the market, especially for projects utilizing the MEAN stack. This makes it easier to deploy than other solutions.
MongoDB is incredibly easy to set up and use. The fact that non-relational DBs are better for more unstructured data, makes it so that you don't necessarily have to know exactly what the end state is going to be before building your schema. Its data throughput is also a key differentiator, so anything with Big Data is going to be a good fit for a non-relational DB and MongoDB, in particular. Finally, the team behind MongoDB is constantly improving the product and releasing updates, and there are several good data viewers in the market, including one from Mongo, for viewing the data and creating queries.
Creating metrics dashboards can be challenging due to the potential need for JOIN queries in your data. Anything that contains these will be harder to aggregate. Their aggregation framework can be hard to use and limiting for certain requirements.
Best No-SQL Database.
MongoDB has no proper structure like rows and columns in RDBMS. There is a feature called indexing where each and every row in the MongoDB database is identified with a unique id. The unique id is provided for each and every new document. The queries are easily understandable without involving any
complex joins, unions. It also obeys the Atomicity, Consistency, Isolation, Durability known as ACID properties which are essential for a database. MongoDB supports sharding means huge data can be divided into smaller data and can be stored in multiple databases across a network. Different collections in MongoDB can be clubbed together and it also supports transactions which involve data needed from multiple documents across a collection. Based on these properties I have worked on different use cases and because of these features, work became simpler.
1) There is no fixed schema like RDBMS. We can alter the table structure insert any number of rows and columns.
2) Data retrieving from this No-SQL database is very much fast when compared to other No-SQL databases.
3) Very easy to install. Provides JSON data support.
4) Can be integrated into different languages like Java, PHP.
5) There are no complex joins of queries like RDBMS.
6) The technical support can be available from MongoDB clients in case of any complex issues that occur while working.
7) Having extra features like a backup of stored data, sharing the data to multiple systems across the network is an added advantage.
8) Handles unstructured data i.e the data which has no format, no proper structure.
I did not find any flaws with this software.
Robust for scaling
We switched from MLabs after MongoDB bought them and have since been able to make much better use of the MongoDB ecosystem with Compass, Charts, stronger cluster configuration etc.
We can see that MongoDB are on a growth-mindset, constantly adding new features like serverless functions, analytical text search, global write ops, and many other at-scale, enterprise level features. Some of these are already helping us reduce our infrastructure costs, for example, we've recently began switching off our third-party search service that was costing us £££ thanks to the introduction of MongoDB search.
We've had some recent headaches around the MongoDB connection string changes and issues with whitelisting some of our private VPNs on AWS. But these are minor issues. I personally think the Performance Advisor feature is poor - it would be far better to get a list of all unindexed queries listed by overall usage by time-period, rather than the adhoc suggestions that we see.
According to my experience with MongoDB it is good NoSQL database. It has good query capacity, Also when we going to solve some business problems some requirements are change when we build the system. At that time we have to change same database collections. MongoDB support it.
Mongo DB is non relational database (NoSQL). It is a document database. it has good query capacity. Very easy to install and setup Mongo DB. Also Mongo DB is schema-free, there fore our software (code) defines the schema. It support BSON data format, there fore no complex to write code with mongo db (most of programming languages support BSON data format. We can index the mongo collections and increase the query performance
When we need to query using two mongo collections (join two collection), we can use lookup feature. but the problem is Mongo DB lookup feature is slow. Also we have no option to run query among two or three collections like as Elastic Search. When we using Elastic Search we can run query among two or three indexes(collections). There for in Elastic Search we can move historical data to separate collections and improve query performance. if we need query with historical, Elastic Search support it. But using Mongo DB we have to handle it in programming side.
MongoDB review, a great, secure, and flexible tool to store your data.
Installing, set it up, and link it with some backends applications.
Customizing hooks, and triggers.
Use of CRUD requests.
MongoDB is a great and fresh database server that allows you to create and use non-relational databases, that means; you can store the data in JSON format object. Being an amazing and handy tool that will be compatible with almost every type of development.
Moreover, MongoDB features cloud services, allowing you to create and use cluster and triggers, also a tool for monitoring. Furthermore, Mongo uses hooks systems that offer you the option of use CRUD requests and customize the behavior of your database and the way that your models interact.
For novices or junior developers, the setup of mongo and its services will be hardy, being essential have some basic knowledge about how MongoDB and the non-relational databases work. For this scenario, MongoDB has a complete, and handy Documentation that explains every service and gives you examples about using the databases and its services.
One of the best NoSQL alternatives to traditional row/column RDBMSs
While my company uses the Microsoft stack (.NET/IIS/SQL Server) for our enterprise development, we use a MERN (MongoDb, Express.js, React and Node.js) stack for most of our internal development (Intranet, sales reporting, ETL, automation, etc.). MongoDb is a key part of the flexibility of this stack, allowing us to model dynamic and complex data very quickly -- a huge advantage working in an agile development environment with short dev cycles and heavy reliance on iteration/refactoring.
Being a NoSQL, document-based database, MongoDb allows me to think about data NOT in terms of rows, columns, tables and keys, but in terms of complex hierarchical JSON-like documents that very closely resemble how the data is presented and used. This is incredibly valuable when quickly stubbing out a new app's feature set and the data requirements for it, with the added advantage that MongoDb works seemlessly within a MEAN/MERN development framework.
Also, the learning curve is greatly shortened by MongoDb University, which is a free set of training courses taught by MongoDb, Inc., Engineers. It's an amazing free resource for the neophyte Mongo developer.
Because MongoDb doesn't have a schema, deeply nested objects can become needlessly complex if the developer doesn't have a strong understanding of hit/her data. Queries requiring joins of complex object structures can be slow in non-optimized, under-powered environments.
Powerful data base that allows high performance, continuous growth and high availability in storage
When working with this database, the expansion became easier and much more economical than the relational data base due to the horizontal scaling, distributing the load across all the nodes, which allowed the organization to store many more data and perform queries. manufacturing very quickly
Queries can be made quickly because the data is connected and interlaced thanks to the ID that is given to each document, the search is simpler; in addition, it has the facility to balance the loads which allows a better storage of files, it does not have to pay for the license, it contains a high security with advanced user management, the semi-structured or structured databases can be easily adapted, you can program the tasks, you have tools for the analysis of the data, using this data base the neck of bottles generated in the relational databases is completely eliminated
When running mongoldb uses all the free RAM which works as the cache, when the amount of data exceeds 100GB it usually has performance problems, when making a copy the verification and the durability is committed, when making a writing on the base of data the same is blocked which drastically reduces the concurrence
Best NoSql database out there
It's a great database and best to learn for someone entering the database world.
It's ease of use and integration with Python is the best thing. Use for web development and other applications, this has been a great tool.
Don't know the cons of this great product. I can say it would be better if they start providing certifications for professionals.
A tool that fits very certain needs
Certain common operations are very very easy to spin up a one-off query for and utilize the data right then and there. In that sense, there is a very lightweight feel to developing with MongoDB at the start of most projects.
The design paradigms around MongoDB make it so that you will eventually want to add some sort of schema-type check somewhere in your stack. This will make development much simpler over time as the data begins to evolve. In general, there's a lot of other scaffolding you will want to do in order to sane-ly use a NoSQL as most people seem to want to (a quick start data store for a project that would otherwise benefit from a relational database). Not saying this is the "correct way" to use MongoDB, but just our experience within a system/framework like Meteor for example.
A great not-too-NoSQL database
I personally used it in project since the day it came out, and honestly some things were really bad, but the biggest barrier was in my teammates head as they rejected the innovation it represented at the time.
MongoDB has been a great product from the start as it brought the simplicity of the NoSQL movement against the old SQL/RDBMs "monsters", but also bringing a host of functionality that made it possible to use it immediately and without too much work in respect of the old RDBMs mindset and feature set.
Setting it up even in a complex environment remains relatively easy, and also using it it's quite straightforward for developers.
3rd-party libraries and framework support is constantly increasing as well.
It has a history of bugs and weird things that made it look bad to some people.
Within the NoSQL databases, probably one of the best
Count on NoSQL database technology, with a free but very useful technology, perfect for handling large amounts of data, making better use of the hardware resources of the applications that require it.
This type of non-relational database is a very useful tool today, where the amount of data handled in the web services are very abundant and a better way to store and take advantage of resources is needed, we use mongoDb, with its noSQL proposal takes better advantage of resources, since no paid licenses are needed, this money is used for hardware power, the expansion is easier since the database should not be restructured, it will keep the files linearly, that the escalation is horizontal and the load is distributed across all the nodes, taking better advantage of the hardware performance making any application more scalable.
It has its weaknesses, but you must know when to use this technology and when to use relational database, there are no transactions so if you need to use it, you should simulate them in a certain way, if it is very required in your application it is better to use sql, either Joins is available, so you should make several queries to interact between the data, you must be careful with this and know what technology is better with the application that will be developed.
The de facto standard for document-based NoSQL databases
MongoDB has made it very easy to rapidly develop and deploy applications that require a document-store based NoSQL database solution.
MongoDB can be hard to set up to support auto-scaling environments, and the best provisioned hosting options are quite expensive.
A database revolution
For non-relational data storage, you really cannot beat MongoDB.
It's incredibly flexible and performant. With rich documents you can keep data in just about any way that makes sense to you. When your data doesn't nicely fit into the relational database format you'll want to use MongoDB. They're constantly developing the database and each version brings more features and better ways of doing things. The aggregation features allow for complex heavy queries to be run very quickly.
It can be a bit complicated to start with and writing aggregations without a great tool to help can be pretty tricky. Some of the features in the earlier versions are slightly limited and miss core requirements like 'join' style queries.
Review of MongoDB
I'm using mongoDB for more than two years and It was great selection when I need to store documents which has unknown structure along with shared structures. That means, it's very easy to save a JSON in mongoDB. This is very helpful when creating embedded databases for java microservices projects using spring boot by adding dependencies via start.spring.io
MongoDB is a schema less database management system and it has a document based structure and can store collection values on documents. It is extremely faster than the relational database management systems and it is a light weight reliable application. And It is very easy to scale while the product is open sourced which is free of charge.
Database joins are not supported since this is a No-sql database.