TrustRadius
https://media.trustradius.com/product-logos/x1/BQ/UA6NT9PUI691.PNGMongoDBReview for MongoDB software2019-06-14T12:23:09.891ZI 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.,6,It's helped to improve overall incomes in my company.
Many employees have been recruited because of this.,MySQL,Angular Feature Flags, Node, Laravel PHP Framework,9Thuvaragan AmarasingamMongoDB: easy to use, easy to shot yourself in the foot2019-03-14T14:27:38.664ZMongoDB 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.,6,There where many errors the clients suffered from due to bad migrations and data structuring.
Development, changes, and migrations where fast.
Migrations where hard to perform in a reliable manner.
The company was able to move forward without a DBA.,PostgreSQL, Amazon DynamoDB, Firebase and Elasticsearch,PostgreSQL, Elasticsearch, Firebase,6Sagiv FrankelOne of the best NoSQL family databases2019-02-28T16:22:17.111ZWe 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,9,Easy to store the raw text data in the form of documents.
Easy integration with Hadoop's other services.
Scalability and availability is not an issue with this.
It doesn't perform well with a high rate of updating on data.,Cassandra,Atlassian Confluence, Datadog, Elasticsearch,9Rounak JangirMongoDB - Best NoSQL Database to Store Unstructured Data2019-02-22T19:04:49.939ZThe 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).,10,Cost us very little to host and manage.
Gives us a powerful datastore for unstructured data, which saves development time having to build similar solutions in a relational database
Very performant (fast), which helps the business run efficiently.,MySQL and PostgreSQL,10Gabriel SamarooMongoDB - Best DocumentDB out there !2019-05-20T16:45:15.363ZWe 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.,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.,9,MongoDB has helped us to save costs by avoiding installing and maintaining the software in-house. We use their Atlas service and thus have freed the need for DBAs.
Migrations are difficult to perform in a reliable manner. On the flip side, they do offer this as a service now.
Lowered development times,Cassandra and Apache Hive,SQL Server Integration Services, Informatica Enterprise Data Integration, JIRA Software,8Verified UserMoved to Mongo and never looked back!2019-04-09T23:01:08.418ZAt 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,10,MongoDB has been fast, easy to scale, and affordable to host.
Even developers coming from SQL have had an easy time adapting to MongoDB.,Redis, Redis Cloud, PostgreSQL, Azure SQL Database, Azure Cosmos DB, SQL Data Warehouse and MySQL,Azure Active Directory, Azure Cosmos DB, Azure SQL Database,10Verified UserOne of the best NoSQL databases you can get2019-03-06T20:17:58.970ZMongoDB 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.,9,Its ease of set up saves us time in our NoSQL database.
The durability of the database gives us peace of mind over not losing data.
It is a great solution for unstructured data.,Amazon DynamoDB and Google Cloud Datastore,Terraform, Puppet Enterprise (formerly Puppet Data Center Automation), Google Cloud SQL,9Verified UserMongoDB is best tool for NoSQL type based database2019-02-28T19:51:18.213ZMongo 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.,9,It helped us to solve business problem for storing flexible schema data.
Replication is very easy and failover works very well.,Microsoft SQL Server,Microsoft SQL Server, Microsoft Access, Oracle Database,9Verified UserMongoDB Review2019-02-23T21:07:18.899ZMongoDB 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.,8,Simplifies the modeling efforts of variable datasets with unstructured data needing storage.
Often requires another database, generally Elastic Search, for anything but the easiest relationship queries.,PostgreSQL, MySQL and Amazon DynamoDB,PostgreSQL, Amazon DynamoDB, MySQL,6Verified UserMongoDB is a safe choice for genomics research project2019-02-23T21:02:58.583ZMy 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.,9,There is little negative impact in using MongoDB in terms of ROI, as it comes with reasonable pricing policies.
In project and workforce management perspective, it is easy to predict the budget since many developers are familiar with MongoDB. We don't need a "special" developer for it, which causes uncertainty of salary for the specialty.
MongoDB runs well with most of operating systems, and that's one aspect that makes the product easy to adopt with minimum expenses.,Cassandra and Hadoop,Cassandra, Hadoop,8Verified UserMongoDB is best NoSQL database software for keeing large data.2019-02-14T15:57:38.636ZThe 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.,No need to write a complicated query such as MySQL. Writing the query in MongoDB is easier as compared to MySQL.
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.,9,Previously my company used firebase which is too costly and after that, they decided to move to MongoDB because of [the reduced] cost
Developers [are] taking less time to query the data.
Very easy and efficient to keep the data in a database.,MySQL,MySQL, PostgreSQL,9Verified UserMongoDB, noSQL, noRelational, noProblem2018-12-14T17:51:34.449ZWe 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.,9,Better development times, this translates into the better distribution of the development team's time
When you work with mongo the learning curve is quite short, since having mongo university they themselves provide the learning of this tool so it is easy to work with this tool, without paying additional cost in courses and trainings.
You do not need to know about command console since you work with a database administrator graphically, like a desktop application,CouchDB,FirebirdSQL, SQLite, Oracle Access Management,10Ronald MelendezMongoDB: Easy and powerful2018-12-22T20:10:43.327ZI 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,8,Data schemas make bringing data to the front end easy
Minimal development time needed to get this running
Different mindset needed if coming from a SQL background,,Google App Engine, Twilio SMS,8Bill HeftyAn excellent option to save your data.2018-12-14T16:59:05.527ZWe use MongoDB in the company's software development department to storage a large set of data for a meteorological forecast application. The data were provided by a third party service and refreshed every 5 minutes. Mongo was chosen to manage all the data. It's also used for a service of dynamic forms developed in the company.,With the ideal performance configuration, MongoDB is a great tool to manage data in a blazing fast way.
The document-oriented database has certain advantages: good fit for modern JavaScript frameworks (direct use of JSON), flexibility, big data processing and real time statistics/data analysis.
MongoDB is very easy to understand.,The resulting database is heavier than in a SQL relational database system,9,We deploy quickly our solution, it was very important because we had a short deadline in this project,Azure SQL Database and RavenDB,Microsoft Visual Studio Team System, Microsoft Azure, 3CX Phone System, Visual Studio IDE,9Miguelangel NuñezDeveloper perspective on MongoDB2018-12-11T00:06:08.328ZFor 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.,9,Being able to get rid of many of our Oracle licenses has saved the company a lot of money. A big part of that was being able to reduce our cores because the load without some of our search calls lowered our requirements significantly. However now that that problem has been solved we don't have any real dependencies holding us to Oracle and are moving everything which will allow us to get rid of the rest of our licenses.,Oracle Database and PostgreSQL,Skype for Business (formerly Lync), Microsoft Office 365, Google Forms,8Brett KnightonIf you want to build a data lake, consider this!2018-12-17T19:44:17.527ZMongoDB is used as part of a security intrusion detection system, which keeps track of security events. These events, or indices, contain data pretaining to security related data, such as authentication, sign in history, etc. There can be a lot of these events and MongoDB is used as a no fuss store that can easily accept all kinds of data from requests we get.,We get a lot of data in, with various schemas depending on the request so MongoDB is a great pool for all the data.
It's simple, and the fact that it's non-relational makes it easy to add data from the pipeline.
Since it's all JSON it's super easy to pass it all into the frontend with a request.,Two edged sword, since it's not a relational db the data is kind of "loosey-goosey" and can be hard to keep track of.
It's newer than something like MySQL, and also has a different use case, but as such has less community support.
Compared to MySQL it's a heavier product.,7,Well worth it to help store data for analytics
We can run it in aws!,MySQL,MySQL, Puppet Enterprise (formerly Puppet Data Center Automation), Slack,8Verified UserA NoSQL database for even the Non-data expert2018-04-02T14:28:48.897ZWe 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.,8,We didn't have to spend time and money on much training in learning database management
It helped us get to market faster with a few different products
We aren't pushing it to any limits yet so I can't give any hard numbers on performance or sharding stats.,Firestore,React, Mandrill, Mailgun, MailChimp, Nexmo, Google Drive,9,I like the javascript nature of the query syntax and API.
Structuring data is just like structuring JSON.
Some sophisticated reporting and querying can be done with relative ease with the Aggregate frameworks.,Relational data joins
Normalized data (though the main usage pattern is to avoid this - sometimes it's hard to avoid, however)
Structuring data for how you need to access it.,8Joshua WeaverMongoDB is a great tool to read large amounts of data.2018-06-04T21:21:45.617ZMongoDB 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.,9,Reducing overall business costs as installation cost is very less of this tool.
Less number of resources needs to maintain it.
Quick and effective response to customers queries and issues.,MySQL, Visual Studio IDE, SoapUI NG Pro,8Nikita kumariIf you want easy management and creation of database, MongoDB should be your choice2018-02-13T19:26:38.865ZI 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.,Performance: MongoDB offers great performance when inserting data much greater than other traditional database systems. However, this advantage involves sacrificing characteristics of relational database systems such as the processing of transactions.
Replication: MongoDB supports the type of master-slave replication. This replication system is simple to understand.
Storage: MongoDB can be used with a file system, taking advantage of the capacity that MongoDB has for load balancing and data replication using multiple servers for file storage.,8,Infrastructure savings
Hardware savings, since mongodb allows access to databases from the cloud.
Easy access to thousands of data, quickly,,MySQL, SQLite, MariaDB,8,Yes,8,No,Once, I had a problem to pass a database to an older version. The MongoDB technical team explained to me step by step everything that
I should do.Fernando MalaveIt is open-source, cross-platform and schema-less.2018-02-09T18:01:50.794ZYeah, 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.,Its file system, indexing to improve search and optimaizatio.i liked its BSON features because of all binary-encoded serialization. its create internally index and map document properties. BSON format is a use of the _id field as pk. it also supports ad-hoc queries by indexing and using a unique query language. It is schema-less as I mention in pros option.,9,investment for future
return and profit
increased productivity of business,my sql,MySQL, Microsoft SQL Server, HBase,8Sonaj GuptaI gotta have more MongoDB!2018-01-30T18:36:51.004ZWe use MongoDB to power our new e-commerce platform. The first feature that we have enabled has been the product catalog search. Thanks to 3.6 change streams we are able to react when a user searches and there are no results. We can even send a text message through Stitch/Twilio integration to send a personal message to the user.,MongoDB offers Stitch, which can replace a lot of backend code through its API. It can also integrate your application with a lot of services such as Twilio.
Change Streams allow you to create responsive applications.
The BI Connector has been redesigned and it has become a lot faster to set up.,Stitch is still in Beta. A few features are still not available. I expect those features to be available in 2018 sometime. Example features missing are Change Streams and $text.,MongoDB Stitch has revolutionized our stack. We can now incorporate so many backend features directly into Stitch that it has been a real pleasure working with the technology. We still use Node.js, but Stitch really reduces development effort.
Change Streams and $jsonSchema are welcome additions. Before, we used to tail the oplog and use the validator introduced in 3.2. Now we have better solutions. Thanks MongoDB!,10,The ease with which applications can transform data in far greater than before. Developer productivity and happiness has gone up.
The integration of applications with third party services has become super easy.,SQL Server and Couchbase Data Platform,Stitch,10Daniele GrazianiMongoDB -- the "Honey Badger" of NoSQL2018-01-12T20:38:01.475ZWe are using MongoDB as the backbone of our latest product offering, the Project Portal (v0.9 released Jan 2016). This is a Saas offering that we essentially white-label to our OEM clients for their customers and end users. MongoDB offers a robust, scalable, simple-to-get-started solution for the persistence layer of our Rails app.,As a software architect, I like the ease with which MongoDB avoids the typical "impedance mismatch" between traditional SQL and the object-oriented problem domain classes. MongoDB (via mongoid) in our Rails app is like a "hot knife through butter." It is much more akin to an OODBMS than anything else.
MongoDB is easy to use throughout product development as it is the "honey badger" of databases. As your product rapidly goes from idea to startup to scaling, MongoDB makes it easier than any SQL database I ever used. You spend more time building your solution, and less time worrying about feeding, nurturing, and migrating the SQL beast.
The ease with which you can spin up replica sets is amazing. No more excuses that you could not build a robust persistence layer. (Especially if you tack on services like MongoDB cloud offerings.)
I also take advantage of the geo-aware spatial indexing. To be able to geocode users, logins, problem domain classes (entities with an address), and do geo-aware queries -- like find me all of the X within Y miles of point Z. Booyah!,I love the idea of Map-Reduce native support in MongoDB. Admittedly I have not used it as much as I would like -- it always seems to trip me up.
Recent additions to the aggregation queries have helped reduce (no pun intended) my need to better wield the weapon that is Map-Reduce.,For my time and money, I would start off almost every project using MongoDB -- even if I knew it might not be the ultimate final DBMS.
Why? Because, in the early stages of product development, I am rapidly iterating on the domain, and other parts of the app. Sometimes changing my mind on major pieces of the architecture as we prototype early solutions.
MongoDB works as freely and as quickly as I do. SQL databases do not. They get in the way, slow me down, tick me off.
However, not all apps are well-suited for NOSQL. So if there are performance needs or other reasons that may point to SQL, then at some point I migrate.
Controversial, I can imagine. But I could explain it over a beer. Or three.,10,Due to MongoDB's honey badger approach to persistence, it allows our teams to run fast at implementing our web apps.
MongoDB is easy to administer -- especially because we use MongoDB Cloud to backup and monitoring.
Admittedly we are not storing gazillions of documents (only 15GB), and we are not "pushing the envelope" on performance, so we do not require any database admins.,CouchDB, MySQL and Microsoft SQL Server,GitHub, IntelliJ IDEA,10Jon KernI'm Liking What I'm Learning2017-10-06T19:04:40.080ZMongoDB 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,MongoDB has been effective at allowing us to store de-normalized data.,9,While there has been a slight learning curve in our DBA group, MongoDB has proven to be a good choice for a document store.,Oracle Database 12c,10Douglas JagodaReview from a database agnostic user2017-09-15T14:52:53.502ZWe used it as our main backend database for a particular platform within a department. It's very good for horizontal scalability. It allows us to scale out instead of scaling up. It is easy to tune and comes well-tuned out of the box. User bases are quite large as well.,sharding
replication
out of the box performance,maturity
documentations
WT stability,MongoDB has very good sharding and replication feature.,6,We are able to scale because of sharding,7Wei Shan AngMongoDB - the game changer2017-09-12T19:29:37.277ZAs 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.,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.,I love the stability and ease of setting up. In an previous project we ran a replica set in a mini IoT device for the automotive industry. There is not complete self healing, but in this environment we have not had one outage in three months of constant usage in a test car.,9,Implementation time could be speeded up
Lowers the cost for hardware due to horizontal scaling
It takes some time to really get really into the business and do a deep dive,,1Michael Höller
Unspecified
MongoDB
270 Ratings
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