Which database is best? MongoDB vs PostgreSQL
SQL or NoSQL? Although these two databases have aspects in common, there is an option more suited to you, depending on the intended use. The following comparison of MongoDB vs PostgreSQL is focused primarily on speed and security factors.
The NoSQL solution scores particularly well if you need a system that can grow along with your requirements. This applies not only to the sheer volume of data, but also to different data types. MongoDB has horizontal scalability, which makes the system the ideal solution in the e-commerce sector, where transaction data has to be transferred quickly and securely. These advantages, paired with its flexibility regarding data types, ensure that MongoDB is an excellent choice for content management systems. If you require configuration options and extensive analysis functions in real time, MongoDB is worth considering.
PostgreSQL is suitable for extensive web applications and provides valuable resources for e-commerce. The system is a good choice for applications in the Cloud and the Internet of Things. PostgreSQL is also highly effective in cooperation with other databases.
In comparison, PostgreSQL follows a relational approach. Although there are numerous NoSQL alternatives, using a table-based system also has its advantages. An important feature of PostgreSQL is that the management system is much more flexible than other SQL options and allows columns with sub values. The database management system also relies on foreign keys and triggers. Queries are made using the classic client-server principle. Files and connections are managed via the central server component ‘postmaster’. Different clients then send their queries. PostgreSQL supports numerous data types, although these must be structured in advance.
PostgreSQL, on the other hand, scales data vertically and therefore cannot quite keep up with the performance of the NoSQL solution. Nevertheless, the performance of the relational system is impressive. It is possible, for example, to perform write and read operations simultaneously. Data authentication and in-depth, low-latency data analysis are also often better with PostgreSQL than with many of its commercial competitors. The database works with complex data types and queries and can therefore also score points when it comes to big data. Additional resources such as memory or CPUs can be added to meet increasing requirements. Features such as just-in-time compilation and table partitioning also help when processing large volumes of data.
The best-known companies that rely on MongoDB include the following:
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MongoDB: Horizontal scaling and maximum flexibility
To understand the different methods involved in this comparison, we’ll give you a brief overview of the MongoDB and PostgreSQL databases themselves. MongoDB owes its name to the English term ‘humongous’. The system was published in 2009 by 10gen (now MongoDB Inc.). It is designed to enable users to manage huge amounts of data in a clear and concise way. So as to make this possible, the NoSQL database is particularly flexible and can be easily scaled. The structured, semi-structured or unstructured data is stored in the JSON-like format BSON in the form of documents. MongoDB was written in C++ and is still distributed worldwide under the open source SSPL. Tip
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PostgreSQL: A supposed oldie with modern advantages
In our MongoDB vs PostgreSQL comparison, the second solution takes a completely different approach. PostgreSQL functions completely relational and cross-platform, though non-relational data types are also supported. The system first appeared in 1996 and is based, at least in part, on databases that have been developed at the University of Berkeley since the 1980s. The system, which is maintained by the PostgreSQL Global Development Group, is still open source today. PostgreSQL claims to be the most advanced open-source database in the world. What is certain is that it is valued worldwide for its flexibility and stability. The management system was written in C and is often simply called ‘Postgres’.What are MongoDB and PostgreSQL used for?
At first glance, our MongoDB vs PostgreSQL comparison seems to suggest both databases could be used for similar purposes. Both solutions are well thought-out, highly functional and comparatively flexible databases that ensure order and overview even when dealing with large or increasing data volumes. A more detailed analysis reveals that companies need to decide according to their own requirements who has the edge in the MongoDB vs PostgreSQL comparison and which database offers the response to their needs.The NoSQL solution scores particularly well if you need a system that can grow along with your requirements. This applies not only to the sheer volume of data, but also to different data types. MongoDB has horizontal scalability, which makes the system the ideal solution in the e-commerce sector, where transaction data has to be transferred quickly and securely. These advantages, paired with its flexibility regarding data types, ensure that MongoDB is an excellent choice for content management systems. If you require configuration options and extensive analysis functions in real time, MongoDB is worth considering.
PostgreSQL is suitable for extensive web applications and provides valuable resources for e-commerce. The system is a good choice for applications in the Cloud and the Internet of Things. PostgreSQL is also highly effective in cooperation with other databases.
Functionality
The paths taken by MongoDB and PostgreSQL to achieve their goals are very different. As a pure NoSQL solution, MongoDB completely dispenses with rigid relational tables and instead works in a document-oriented manner. These binary JSON documents (called BSON) are then summarised in collections. The system relies on key-value pairs. The key here consists of a character string; the values can be other documents, Boolean values, numbers or completely different file types. The structure of a JSON document can be easily changed by deleting or adding individual fields. A text search is provided to identify specific documents. Structured, semi-structured and unstructured data is taken into account.In comparison, PostgreSQL follows a relational approach. Although there are numerous NoSQL alternatives, using a table-based system also has its advantages. An important feature of PostgreSQL is that the management system is much more flexible than other SQL options and allows columns with sub values. The database management system also relies on foreign keys and triggers. Queries are made using the classic client-server principle. Files and connections are managed via the central server component ‘postmaster’. Different clients then send their queries. PostgreSQL supports numerous data types, although these must be structured in advance.
Performance
MongoDB’s name suggests it can handle huge amounts of data without any major issues. The system absolutely lives up to this claim. The database is horizontally scalable and not dependent on the computing power of an individual machine. Thanks to the combination of options with a wide range of hardware, there are theoretically no limits to its performance and storage volume. Even when numerous users are accessing data all at the same time, the query speed remains high. Sharding distributes the load across different computers. This not only contributes to better performance, but also offers the best possible protection against possible server failures.PostgreSQL, on the other hand, scales data vertically and therefore cannot quite keep up with the performance of the NoSQL solution. Nevertheless, the performance of the relational system is impressive. It is possible, for example, to perform write and read operations simultaneously. Data authentication and in-depth, low-latency data analysis are also often better with PostgreSQL than with many of its commercial competitors. The database works with complex data types and queries and can therefore also score points when it comes to big data. Additional resources such as memory or CPUs can be added to meet increasing requirements. Features such as just-in-time compilation and table partitioning also help when processing large volumes of data.
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Compatibility
Both solutions work across platforms and can therefore be used on Linux, macOS, Solaris and Windows. PostgreSQL goes even further and also works on FreeBSD, HP-UX, NetBSD and OpenBSD. The SQL database is ACID-compliant by nature (Atomicity, Consistency, Isolation, Durability), while MongoDB at least offers this option. Both systems support numerous programming languages, whereby the choice in the MongoDB vs PostgreSQL comparison is significantly greater with the younger system.Programming language | Supported by Mongo DB | Supported by PostgreSQL |
---|---|---|
Actionscript | ||
C | ||
C# | ||
C++ | ||
Clojure | ||
ColdFusion | ||
D | ||
Dart | ||
Delphi | ||
Erlang | ||
Go | ||
Groovy | ||
Haskell | ||
Java | ||
JavaScript | ||
Kotlin | ||
Lisp | ||
Lua | ||
MatLab | ||
.net | ||
Perl | ||
PHP | ||
PowerShell | ||
Prolog | ||
Python | ||
R | ||
Ruby | ||
Scala | ||
Smalltalk | ||
Swift | ||
Tcl |
Security
One of the most important reasons why users opt for PostgreSQL is the database’s strong security architecture. This includes the Lightweight Directory Access Protocol (LDAP) and a Pluggable Authentication Module (PAM) as well as host-based authentication, data encryption and SSL certificates. The predefined database structure also ensures that your data is always protected in the best possible way. MongoDB also has numerous security features, including encryption at field level and on the client side. The distribution to different servers also offers at least a high level of reliability and ensures that data is available again without major delays.What are the various versions of MongoDB and PostgreSQL?
One of the similarities between MongoDB and PostgreSQL is their open-source approach. Both systems are therefore not only open source, but also available free of charge, at least in their basic version. Although this also means that there is no professional support in this case, two dedicated communities make up for this shortcoming and are also happy to advise newcomers. The documentation and expansion options are also somewhat more extensive due to the longer market maturity of PostgreSQL. MongoDB also offers various Pro versions. The ‘Enterprise’ and ‘Atlas’ versions (for cloud use) are subject to a fee, but also have some additional features and comprehensive support.Which companies use the two databases?
Even if the MongoDB vs PostgreSQL comparison shows that the two solutions pursue two very different approaches, they still have one thing in common, which is that numerous large companies rely entirely or partially on the services and advantages that the two databases offer them.The best-known companies that rely on MongoDB include the following:
- Adobe
- Amadeus
- AppScale
- Craftbase
- Disney
- Etsy
- Foursquare
- Lyft
- MTV
- The New York Times
- Via Varejo
- Apple
- IMDB
- Runkeeper
- Skype
- Spotify
- Twitch
Tip
Would you like to find out more about database systems? In our Digital Guide, we also compare MariaDB vs MySQL, present the best open source databases and offer you a detailed MongoDB tutorial.