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.
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PostgreSQL
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PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
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Fully managed, global cloud database on AWS, Azure, and GCP
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for …
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your …
Both Couchbase and MongoDB are document-oriented NoSQL databases, so they have very similar features. While they do have some fundamental differences in terms of how they scale, shard, etc. the one key reason why we went with MongoDB is its availability and support from the …
The flexible structure underlying MongoDB's construction is not found in other competitors; the ability to easily change the structure without affecting other stored documents. It is very ideal for projects that you cannot predict that the structure will change this way. Of …
Implementing new features for application becomes simpler with MongoDB since you don't need to run database migration scripts just to for example add new fields to database only to store some extra data. This is especially good for the deployment phase. Only new version of …
MongoDB is a robust and scalable db which offers a lot of cool features out of the box. Being open sourced and backed by a great community with developer tools like mongo compass , it was a no-brainer to go for it. It has connectors in almost all programming languages and is a …
I would say Cassandra is better than MongoDB since it has the backing of Facebook to it. Its inherent properties like versioning put it into the other category of columnar databases, but it's one of the NoSQL databases which you should definitely consider for your organization …
This tool is only capable of reading real-time data very smoothly. The transition was also pretty easy and quick. Syntax is also very easy and comfortable to learn and use.
The main reason for selecting is that it works very fast under the Intellijet module environment and we …
In our early development days we weighed NoSQL databases like MongoDB with RDBMS solutions like MySQL. We were more familiar with MySQL from past experience but also were wary of painful data migrations that slowed down development iterations and increased the risk of outages …
Snowflake and Redshift are much more mature and have been around longer. MongoDB is definitely much less expensive and if you are in a startup, this is an almost for-sure option. Redshift can be slow and Mongo is much faster. However, losing the relational database aspect could …
It's very fast and easiest to use. Many companies are using this nowadays. It's helped to complete many software products very quickly so the year income has increased compared with last years. Many programmers are now leaning this tool as back end developers so that we changed …
MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most …
Your default choice should not be MongoDB in my opinion. Most user-facing systems are relational by nature so a well known and reliable SQL database would be easier to maintain and simpler to develop long term. If you highly value speed of development go with firebase. If you …
It does not belong to certain cloud platforms. MongoDB is an independent program that works with any cloud platform including Amazon Web Services and the Google Cloud Platform. For companies who want to maintain a cloud agnostic structure, MongoDB is a great choice for NoSQL …
MongoDB and Cassandra are both database system from the NoSQL family. MongoDB can be used in lots of use cases while Cassandra has a specific usage. There are some features that MongoDB provides efficiently while Cassandra doesn't and vice-versa. Like, you can update the data …
We tend to choose MongoDB when we're faced with a particular situation: we know that we need a NoSQL database in general, and want an open-source implementation that allows us to prevent against platform lock-in. Amazon's new DocumentDB product even allows us to choose to use …
First It's open source and it's cost-effective compared to other databases.PostgreSQL can be easily integrated with numerous platforms. It is well known and appreciated so relying on it as our system database can be easily accepted by our customers. And if your developing a …
For our use cases, PostgreSQL is just as feature rich as other options, costs less, and is simple to get up and running. There is also a plethora of documentation to support it which makes it a great option for a small scale startup without needing high levels of expertise to …
In this case, Postgres is preferred because it handles large data sets and requires fewer hardware resources than its competitor, MySQL. Compared to PostgreSQL, Microsoft products are excellent, but the installation process for MS SQL is lengthy. PostgreSQL has an advantage …
I've been using different databases for the past 20 years, solutions like MS SQL Server, MySQL, MariaDB, Interbase, Firebird, DB2, etc., and by using them I wasn't able to be neither close to the performance PostgreSQL deliver. Also, it is one of the most popular databases on …
Although the competition between the different databases is increasingly aggressive in the sense that they provide many improvements, new functionalities, compatibility with complementary components or environments, in some cases it requires that it be followed within the same …
We evaluated both PostgreSQL and MySQL, two popular open source relational databases. While they are very similar in most areas, PostgreSQL's reliability and performance won us over, plus it has much better support from cloud vendors we also work with.
Postgres stacks up just [fine] along the other big players in the RDBMS world. It's very popular for a reason. It's very close to mySQL in terms of cost and features - I'd pick either solution and be just as happy. Compared to Oracle it is a MUCH cheaper solution that is just …
A free corporate professional product. Who does not want to have such a thing, we hesitated because we did not know the product before and frankly we did not want it at first. But when we give it a chance, it has been running smoothly for years.
When we were originally evaluating Redshift we ran into some issue with dates. Either way, Postgres is a better choice than Redshift because it avoids vendor lockin. We ended up choosing Postgres over MySQL because it was easier at the time to get a hosted Postgres cluster up …
As I have been telling all along, PostgreSQL is much cheaper compared to the other RDBMS solutions. It has got better performance with some of the application services that we are using and is easy to maintain. Overall, we are satisfied migrating to PostgreSQL database clusters.
Much more mature and stable when compared to MySQL with features such as MVCC, complex subquery plans, ORDBMS, and NoSQL support. With Oracle retaining rights to MySQL its future as an open database is less secure and is no longer in the hands of the community. PostgreSQL also …
Its main characteristic is the integrity of the data. In addition, being free software, it has no costs associated with its license, which allows the number of installations to be scaled without problems.
The technical staff quickly learns about its installation, configuration …
Both Oracle and MS-SQL database option fell when we evaluated the effect on our overall solution cost to our customers. customer examine the overall cost of the solution they buy, selecting Oracle or MS-SQL would leave less money in our pockets. We are Linux based solutions and …
PostgrPostgreSQL as a transaction db engine against oracle and sql server works well. TPM wise compared to MySQL and MariaDB, on an evan scale. SQL function supports, far outweighs compared to MySQL and MariaDB. PG Extensions allow for flexibiltity and scalability. Allows …
We selected PostgreSQL due to the number of employees who have used it in the past. The data consistency guarantees. The multiple transaction isolation levels support.
PostgreSQL outperforms every other option. It is faster, more flexible, more reliable, easier to maintain, and more consistent in behaviour than any of the other offerings.
The main reason for select PostgreSQL against MS SQL Server Express edition is the necessity to use open-source platform, without any issues for licensing, client licensing, etc. etc, which is usually follows developers and project managers when they start to use products and …
SQL Server is an excellent product from Microsoft, it is a derivative from Sybase which originally developed the SQL Server form Unix and Linux, and Microsoft purchased it to migrate the DBMS to Windows Server. But the cycle comes full circle, and now Microsoft recommends its …
It's a viable alternative, with a rich feature set and a reliable system. PostgreSQL is one of the best RDBMS's currently on the market in 2020, it serves just as well as a starter, PoC DB for any software idea as a final, highly valuable database solution for big systems.
MySQL: As I mentioned before, MySQL has superior write performance. However, Postgres has super read performance and safer ACID transactions, i.e. less potential data loss. Elasticsearch: we use Elasticsearch to store free-form customer data, but that's a different use-case. …
PostgreSQL is rich in features and free to use which is perfect for our organization. PostgreSQL is our goto RDBMS if we want to create an application or services backend with the database if there's no specific requirement. For example for the most important and largest …
PostgreSQL beats every other RDBMS offering for being truly Open Source. Since it does not belong to a specific company it is poised to remain as such for a long time to come. PostgreSQL has a huge user base and active community. The releases are coming out often with …
MongoDB [is] great at storing JSON data grouped into "collections". In this format, you can store any JSON documents and conveniently categorize them by collections. The JSON document contained in MongoDB is called binary JSON or BSON and, like any other document in this format, is unstructured. Therefore, unlike traditional DBMS, any kind of data can be stored in collections, and this flexibility is combined with the horizontal scalability of the database. It should be noted that MongoDB does not have links between documents and “collections” (this is partially compensated by the Database Reference - links in the DBMS, but this does not completely solve the problem). As a result, a situation arises in which there is a certain set of data that is not related to other information in the database, and there is no way to combine data from different documents. In SQL systems, this would be an elementary task.
PostgreSQL is ideal for handling databases that contain large volumes of information due to its efficiency, speed and above all because of the good management it makes of our resources, it also behaves very well in distributed environments of high demand, if you want a database of stable data and excellent performance PostgreSQL is one of the best.
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.
The performance of PostgreSQL has been enhanced through the years, but always is better to have as much performance as we can.
The replication services could be done directly within the database, and more easily.
The Object Orientation of the Database could be extended, and albeit it manages inheritance of tables, and accepts XML and JSON as primary types, it would be wonderful if one could attach methods more easily to tables (to make them more like classes), and instances (rows for example).
MongoDB is one of the most famous non-relational databases in the world, there are famous active projects that use this database. I think that the same company that develops the database gives you the online induction totally free is something that really is very positive. Accounts with a first-class support to be able to relate the correct implementation of the database, in addition to teaching you the best practices to optimize your projects, I believe that with this decision it is more than obvious which is the best decision at the time of seeing with which database to work.
It is one of the reasons why we prefer it to store documents in a JSON-style format, to access the desired document very quickly regardless of its size, to be readable by human eyes, and to be easily scalable and manageable.
Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.
The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.
I have reached multiple times to the MongoDB community for the help and they have provided each and easy solution for every problem. Over the internet and on stack overflow many people responds over the challenges. Now this tool is very much used in every company and projects so internally many people are there to give a support.
AWS, Heroku, and Digital Ocean all provide Postgres-as-a-service, where you pretty much never need to administrate it yourself but they do it for you. The Postgres community also has developed awesome and reasonably priced extensions, such as Citus DB and CockroachDB in case you need additional support for running it. If you need documentation, Postgres's docs are super thorough and their official forms are active.
The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for quick retrieval later. This is something we can't easily do with MySQL. On this smaller database, MongoDB also lets us retrieve data more quickly with its fast and efficient querying.
In this case, Postgres is preferred because it handles large data sets and requires fewer hardware resources than its competitor, MySQL. Compared to PostgreSQL, Microsoft products are excellent, but the installation process for MS SQL is lengthy. PostgreSQL has an advantage over its competitors in that it can adapt or configure third-party programs, applications, or settings.
We can make more open and flexible systems due to its easy adaptation to new evolutions in web applications.
In the latest versions it offers support for different transactions and we could carry out real tests related to the concurrency of the application.
MongoDB allows you to have distributed clusters, which improves the speed of the queries by reducing the latency that exists between the database cluster and the service that executes the query.
Easy to administer so our DevOps team has only ever used minimal time to setup, tune, and maintain.
Easy to interface with so our Engineering team has only ever used minimal time to query or modify the database. Getting the data is straightforward, what we do with it is the bigger concern.