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Nice for devs, killing operators
What do you like best about the product?
JSON like console language eases a lot the daily life
What do you dislike about the product?
Privilege escalation, PRODUCT-101 a lot of small things that are really annoying, e.g. privilege escalation
What problems is the product solving and how is that benefiting you?
additioal database for our database portfolio
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outstanding performance
What do you like best about the product?
Performance and ability to manipulate data very easily without thinking of relationships.
What do you dislike about the product?
I recently started using mongodb and did not face any issue yet.
What problems is the product solving and how is that benefiting you?
user ui configuration data. also looking to start storing large data from multiple high frequency real-time feeds as an alternative to rdbms
Precision enforced
What do you like best about the product?
I love that I'm never saving the wrong document because my model and the engine enforces the correct settings.
What do you dislike about the product?
I don't dislike MongoDB at all. I wouldn't want to use another database.
What problems is the product solving and how is that benefiting you?
Creating platforms. Model flexibility.
Data is stored naturally
What do you like best about the product?
Ease of use; the online training is available and so easy to learn.
What do you dislike about the product?
nothing as of now, as i am learning the tool
What problems is the product solving and how is that benefiting you?
ease of use
MongoDB
What do you like best about the product?
product, auto scaling, schema less, cost less
What do you dislike about the product?
less flexibility with Json, data sizing, data query
What problems is the product solving and how is that benefiting you?
nothing yet
PM of the distribution platform using MongoDB
What do you like best about the product?
1) Don't need to worry of relationshiops
2) Scalable
3) Fast
4) Allows to store complex structures
5) Excellent support
2) Scalable
3) Fast
4) Allows to store complex structures
5) Excellent support
What do you dislike about the product?
Sometimes the time to release the feature we need is too long, so we have to apply the work around
Not so easily back-tracking meaning that it takes an extra time to investigate what is going on
Not so easily back-tracking meaning that it takes an extra time to investigate what is going on
What problems is the product solving and how is that benefiting you?
1) Big data storage
2) Enterprise segment support
3) Complex data structures storage solutions
2) Enterprise segment support
3) Complex data structures storage solutions
Most intuitive storage solution I've used.
What do you like best about the product?
Easy to set up, intuitive query language, high performing and incredibly reliable.
What do you dislike about the product?
Aggregation framework is relatively slow.
What problems is the product solving and how is that benefiting you?
Large scale aggregation and distribution of common data across global footprint.
MongoDB review SUreshg
What do you like best about the product?
SImple to setup, and flexible architecture.
What do you dislike about the product?
no it works as exopected and not really hard to set up.
What problems is the product solving and how is that benefiting you?
No regular data streaming
Recommendations to others considering the product:
Easy to use, cheap cost and excellent custoer support.
good database
What do you like best about the product?
replication is easy, sharding is very easy too.
Replication
MongoDB provides high availability with replica sets.[9] A replica set consists of two or more copies of the data. Each replica set member may act in the role of primary or secondary replica at any time. All writes and reads are done on the primary replica by default. Secondary replicas maintain a copy of the data of the primary using built-in replication. When a primary replica fails, the replica set automatically conducts an election process to determine which secondary should become the primary. Secondaries can optionally serve read operations, but that data is only eventually consistent by default.
Load balancing[10]
MongoDB scales horizontally using sharding. The user chooses a shard key, which determines how the data in a collection will be distributed. The data is split into ranges (based on the shard key) and distributed across multiple shards. (A shard is a master with one or more slaves.). Alternatively, the shard key can be hashed to map to a shard – enabling an even data distribution.
MongoDB can run over multiple servers, balancing the load or duplicating data to keep the system up and running in case of hardware failure.
File storage
MongoDB can be used as a file system, called GridFS, with load balancing and data replication features over multiple machines for storing files.
This function, called grid file system,[11] is included with MongoDB drivers. MongoDB exposes functions for file manipulation and content to developers. GridFS can be accessed using mongofiles utility or plugins for Nginx[12] and lighttpd.[13] GridFS divides a file into parts, or chunks, and stores each of those chunks as a separate document.[14]
Aggregation
MapReduce can be used for batch processing of data and aggregation operations.
The aggregation framework enables users to obtain the kind of results for which the SQL GROUP BY clause is used. Aggregation operators can be strung together to form a pipeline – analogous to Unix pipes. The aggregation framework includes the $lookup operator which can join documents from multiple documents, as well as statistical operators such as standard deviation.
Replication
MongoDB provides high availability with replica sets.[9] A replica set consists of two or more copies of the data. Each replica set member may act in the role of primary or secondary replica at any time. All writes and reads are done on the primary replica by default. Secondary replicas maintain a copy of the data of the primary using built-in replication. When a primary replica fails, the replica set automatically conducts an election process to determine which secondary should become the primary. Secondaries can optionally serve read operations, but that data is only eventually consistent by default.
Load balancing[10]
MongoDB scales horizontally using sharding. The user chooses a shard key, which determines how the data in a collection will be distributed. The data is split into ranges (based on the shard key) and distributed across multiple shards. (A shard is a master with one or more slaves.). Alternatively, the shard key can be hashed to map to a shard – enabling an even data distribution.
MongoDB can run over multiple servers, balancing the load or duplicating data to keep the system up and running in case of hardware failure.
File storage
MongoDB can be used as a file system, called GridFS, with load balancing and data replication features over multiple machines for storing files.
This function, called grid file system,[11] is included with MongoDB drivers. MongoDB exposes functions for file manipulation and content to developers. GridFS can be accessed using mongofiles utility or plugins for Nginx[12] and lighttpd.[13] GridFS divides a file into parts, or chunks, and stores each of those chunks as a separate document.[14]
Aggregation
MapReduce can be used for batch processing of data and aggregation operations.
The aggregation framework enables users to obtain the kind of results for which the SQL GROUP BY clause is used. Aggregation operators can be strung together to form a pipeline – analogous to Unix pipes. The aggregation framework includes the $lookup operator which can join documents from multiple documents, as well as statistical operators such as standard deviation.
What do you dislike about the product?
MongoDB is not relational so you lose all the capabilities of relational databases.
No joins. You design as if they were never an option.
It scales well in a narrow range but other NoSQL solutions are better at scaling. Sharding is annoying, complex and seems like it was bolted on.
It uses eventual consistency, which is good and bad.
No transactions except at the record level. If you want a transaction you have to fit the whole transaction into a single record.
Hard to secure properly without going with an Enterprise license.
There is no patching, you have to do full upgrades and full upgrades are issued several times a year. So you have to build a patch schedule around those. There is no guarantee that your upgrade will work with your given driver so tests must be scheduled before upgrading.
No joins. You design as if they were never an option.
It scales well in a narrow range but other NoSQL solutions are better at scaling. Sharding is annoying, complex and seems like it was bolted on.
It uses eventual consistency, which is good and bad.
No transactions except at the record level. If you want a transaction you have to fit the whole transaction into a single record.
Hard to secure properly without going with an Enterprise license.
There is no patching, you have to do full upgrades and full upgrades are issued several times a year. So you have to build a patch schedule around those. There is no guarantee that your upgrade will work with your given driver so tests must be scheduled before upgrading.
What problems is the product solving and how is that benefiting you?
messaging make easy
Not a fun read
What do you like best about the product?
the ability to scale horizontally when work loads reach that level
What do you dislike about the product?
everything about mongo and how crappy wiredtiger is compared to mmapv1 with spead mongo is unable to handle our work loads mongos dies all the time
What problems is the product solving and how is that benefiting you?
storing user journeys on massive scale using mongo that there is a lot more better databases out there for certain purposes we should be using
Recommendations to others considering the product:
Be afraid, be very afraid. Do you research. Make sure it's the best product for your work load / use case.
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