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{"title":"The database as a programmer would like it to be"}
What do you like best about the product?
The synergy between the code and database, especially with Node.js.
What do you dislike about the product?
Having to go back and make performance tweaks to existing structures.
What problems is the product solving and how is that benefiting you?
Trying not to spend too much time integrating new features and iterating on existing ones because of database constraints.
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Flexible, Fast, Easy to Setup
What do you like best about the product?
The Schemaless design makes rapid prototyping and iteration incredibly easy. The free tier platforms make it a great option for trying out and can take you incredibly far though there are great options/support provided for Enterprise services. For programmers, there are many well-maintained libraries for wrapping around the API.
What do you dislike about the product?
Though the database itself is fantastic, the third party tools to manage DBs are only ok. They are improving, but tools like 3T and Robomongo don't take complete advantage of the schemaless model.
What problems is the product solving and how is that benefiting you?
Data backups, restoring instances, and fast-paced products are all made easier with Mongo.
Recommendations to others considering the product:
Make sure you read above the vulnerabilities of unsecured Mongo instances and don't get your data kidnapped!
MongoDB ruined SQL databases for me
What do you like best about the product?
The flexibility of document focused databases makes it easy to change or update schemas, hold data with varying sample rates or different, non-subset fields.
What do you dislike about the product?
High performance drivers to native data structures in other programming languages. Specifically, if I want to store time series data in Mongo, then retrieve in Python, the list of queries has to be iterated through to pull out the individual data fields. Some third party solutions provide a better solution.
What problems is the product solving and how is that benefiting you?
Data storage for IoT applications. SQL is certainly popular with business insight applications, but rolling out new and developing products in a start up meant we could not future proof our data collection up front when working with SQL databases.
Recommendations to others considering the product:
Be sure to start with later versions of MongoDB, updates in the last year have really improved indexing performance and flexibility of aggregations. Some SaaS deployments of MongoDB are too far behind.
Quick, reliable NoSQL solution
What do you like best about the product?
MongoDB is really very good NoSQL database. It is simple but powerful. It is quick on large datasets and simple to retrieve data. We use it mainly for logs and statistics data. Where our SQL-based database it uneffective Mongo comes and helps us.
What do you dislike about the product?
If you newer worked with NoSQL DBs it would be a little bit unusually to use it but perfect documentation and simple (JS-based) query language helps you to start quick.
What problems is the product solving and how is that benefiting you?
MongoDB is used for statistics and logs data. Store that in SQL DB is very resourse expensive and uneffective.
Recommendations to others considering the product:
If you have a lot of unstructured data such as logs you should give MongoDB a try!
MongoDB and itds new cool features!
What do you like best about the product?
There are many new cool features which came with MongoDB 3.4. Here are my favorites:
* Native Graph Processing - special purpose graph databases do a good job at storing and querying graph data. But often you want traverse graph data directly in the database. With MongoDB you can process, query, and analyze in real time, without the complexity of duplicating data across two separate databases.
* Improvements for Visualizing MongoDB Data - The complete connector has been reworked and offers now improvements in performance and scalability.
And there will be exiting news of the upcoming version 3.6:
For increasing performance:
- Wire Protocol Compression
- OP_MSG
Introduction of Session:
- Retryable Writes (this is my favorite)
- Causally Consistent Reads
- Notification API
* Native Graph Processing - special purpose graph databases do a good job at storing and querying graph data. But often you want traverse graph data directly in the database. With MongoDB you can process, query, and analyze in real time, without the complexity of duplicating data across two separate databases.
* Improvements for Visualizing MongoDB Data - The complete connector has been reworked and offers now improvements in performance and scalability.
And there will be exiting news of the upcoming version 3.6:
For increasing performance:
- Wire Protocol Compression
- OP_MSG
Introduction of Session:
- Retryable Writes (this is my favorite)
- Causally Consistent Reads
- Notification API
What do you dislike about the product?
Sometimes I struggle over the javascript syntax which is intensely used and some time a little bit unhandy.
What problems is the product solving and how is that benefiting you?
I deal with huge databases, especially the connection to Spark and the new BI Connector in combination with the new aggregation functions helped me already to get things done faster than in the past.
Recommendations to others considering the product:
Get ready to understand the concepts of noSQL databases first.
Understand to "Think in documents". If not you may have a rough start.
Understand to "Think in documents". If not you may have a rough start.
Somewhere between SQL and NoSQL
What do you like best about the product?
Free to add or change fields
Fast performance
Compression (starting with WT)
Fast performance
Compression (starting with WT)
What do you dislike about the product?
w=0, default handling in earlier versions
in earlier versions, the disk usage was quite high (about 10x the actual size)
in earlier versions, the disk usage was quite high (about 10x the actual size)
What problems is the product solving and how is that benefiting you?
Storing session data
Analytics
Analytics
Recommendations to others considering the product:
Store everything in one object, do not use the SQL split into different tables paradigm, because Mongo only in the latest versions has added support for queries with JOIN. ($lookup)
Lifesaver or at least product-saver
What do you like best about the product?
MongoDB is very easy to learn and the BSON format make is super clear to read and interact with.
The most important for us was the sharding feature and the fact we could take advantage of atomic operations.
The most important for us was the sharding feature and the fact we could take advantage of atomic operations.
What do you dislike about the product?
It's not a general purpose DB and you need to plan heavily before creating new db schema.
What problems is the product solving and how is that benefiting you?
We were have a lot of performance problems with our write-heavy application and MongoDB helped us save all those problems. The installation and maintenance was also very straight-forward and we were able to pick it up with ease from the online documentation.
Not a silver bullet, but definitely bronze
What do you like best about the product?
Easiest document database with real querying capabilities with map and reduce built in.
What do you dislike about the product?
Update queries get really slow and database performance starts falling linearly with the size of database
What problems is the product solving and how is that benefiting you?
Workflow management with jobs and task tracking. Product catalog with the evolving schema of products.
Recommendations to others considering the product:
It would be wise to design the db in a way that makes optimization of queries or database writes possible. Since it is a nosql document store it is easy to design badly and therefore needs special attention from early on
Most mature open source NoSQL database
What do you like best about the product?
MongoDB is a versatile NoSQL database, that requires limited training to get started. Querying the database doesn't involve writing complex code, but simply sending a JSON filter.
What do you dislike about the product?
Setting up a production system can be rather expensive for small systems. Setup and maintenance can also be rather complicated without paid tools.
What problems is the product solving and how is that benefiting you?
MongoDB has a dynamic schema. This give flexibility to the application, making it possible to easily create backward- and forward compatible versions. The schema does allow the creation of indexes, to increase performance.
Recommendations to others considering the product:
MongoDB can be tricky to setup and maintain. I recommend taking a course and/or using a SAAS product.
No sql Database
What do you like best about the product?
Mongodb does not have primary Key and foreign key concept which makes it better than SQL database.
It has relationship between tables and which can be related easily.
It has npm packages to integrate to Nodejs server.
It has mongodb driver npm package to access all native methods
It has packages for auto-populate and auto-delete(soft delete)
It has relationship between tables and which can be related easily.
It has npm packages to integrate to Nodejs server.
It has mongodb driver npm package to access all native methods
It has packages for auto-populate and auto-delete(soft delete)
What do you dislike about the product?
It is not easy to sort the result that is json according to the front-end developer.
It does not use elastic search.
Validating the sub-schema is hard.
It is not easy to join two tables (map-reduce)
It does not use elastic search.
Validating the sub-schema is hard.
It is not easy to join two tables (map-reduce)
What problems is the product solving and how is that benefiting you?
Faster database operations.
Easy to write database queries via NPM packages.
Easy to relate tables that is establish relationship between tables.
Easy to write database queries via NPM packages.
Easy to relate tables that is establish relationship between tables.
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