5 Open Source Databases in Com­par­is­on

To ensure smooth op­er­a­tions, careful and struc­tured storage and ware­hous­ing of all data, and the as­sign­ment and control of access rights, a good database is essential for most companies. This has been the case for a long time, as has the fact that main­tain­ing these databases has been as­so­ci­ated with high costs. In the meantime, there are more and more open source databases that not only function reliably, but also offer great saving potential. Which open source databases are available, their ad­vant­ages and dis­ad­vant­ages, and which provider is the right one for your purposes can be dis­covered in our database com­par­is­on.

When deciding which open source database is the right one for your purposes, many factors play a role. For example, is your focus on speed, the pro­cessing of large data sets, or is the exchange with the community par­tic­u­larly important to you? In the following table, you can see our open source database systems com­par­is­on. You can easily decide which is the right option for you.

The main argument for switching to one of the numerous open source databases is, of course, the cost factor. Depending on the company, structure, and provider, a classic database system can cost a re­l­at­ively large amount of money, while the open source options often result in con­sid­er­able savings. This is a weighty reason for many users, but not the only one. In­de­pend­ence can also be a deciding factor. Most open source databases are com­pat­ible with common operating systems and are also open to further de­vel­op­ment. So if a company grows, in most cases the database system can grow with it.

In addition, when it comes to open source code, the exchange with the community is in­ter­est­ing for many. Errors and security gaps are usually quickly dis­covered and corrected. This reason is one of the many that make companies want to switch to the open variant. Of course, this does not auto­mat­ic­ally mean that free is ne­ces­sar­ily better. It makes sense to compare the free databases.

There is a huge number of different open source databases in com­par­is­on to the few large providers that have long divided the market among them­selves. On the one hand, there are as­so­ci­ations of motivated de­velopers who are looking for in­nov­at­ive and reliable solutions, thus creating new options for companies. On the other hand, there are also those providers who pursue a com­mer­cial approach, but draw on the input of an in­ter­ested community. These databases are often divided into free basic models on the one hand and paid deluxe versions on the other. In the following, we present five re­com­mend­able open source databases.

Post­gr­eSQL is an oldie in the field of open source databases. After all, the origins of the object-re­la­tion­al database man­age­ment system go back to the 1980s. However, it is by no means outdated. Rather, the software under BSD license has been able to grow and improve steadily over the years and is largely com­pat­ible with the SQL standard. The open source database can be used platform-in­de­pend­ently, whereby client and server can run on different systems. Post­gr­eSQL can be easily and un­prob­lem­at­ic­ally expanded and adapted, which is why numerous large companies also rely on the database.

Es­pe­cially with par­tic­u­larly large data volumes, open source databases can quickly reach their limits. An explicit exception in that regard is Apache Cassandra. The database man­age­ment system is based on Java and impresses with its zero tolerance for downtimes. In 2008, the system was released by Facebook, today it has its own query language. Apache Cassandra is a column-ori­ent­ated NoSQL database and dis­trib­utes the huge amounts of data to different clusters. Apache Cassandra also scores high in analytics and logging compared to other open source databases.

MongoDB is another NoSQL database. It excels in handling mobile apps, product cata­logues, and content man­age­ment, among other things. The document-based database runs on various operating systems, whereby the data is stored with MongoDB in the BSON format in so-called col­lec­tions. Because these are dis­trib­uted across different servers, avail­ab­il­ity is increased, and the data load is spread across several shoulders. Since its initial release in 2009, MongoDB has been steadily developed further and is now one of the most popular and most widely used NoSQL database systems in the world. In addition to the free open source variant, there is also a com­mer­cial version with ad­di­tion­al features for companies.

However, if it is to be an SQL database after all, many companies swear by MySQL. The database man­age­ment system, which has been available since 1995, impresses with its very simple and intuitive ad­min­is­tra­tion and quick in­stall­a­tion on various operating systems. Main­tain­ing the system is also easy. Un­for­tu­nately, many ad­di­tion­al features, some of which are in­dis­pens­able for ideal use at the highest level, are only available in the paid version. When it comes to data security and mon­it­or­ing, the free database reveals its weak­nesses.

The database server MariaDB comes from the same de­velopers as MySQL and also includes all security patches of the older database. MariaDB functions similarly in terms of use and can also offer MySQL functions. The mentioned paid features can still be found here for free use. Due to the large community in the back­ground, MariaDB is con­stantly advancing and thus comes up with new features. An engine for dis­trib­uted trans­ac­tions, a higher speed compared to MySQL, dynamic columns, and much more ensure that the database does not hold back in com­par­is­on to other database systems.

The in-memory database Redis also works non-re­la­tion­ally and thus belongs to the NoSQL family. The database is par­tic­u­larly im­press­ive due to its speed (with response times of less than one mil­li­second) and its par­tic­u­larly simple use. Many companies swear by Redis, par­tic­u­larly in the domain of caching. On the other hand, there are de­duc­tions in the handling of more complex data struc­tures. Since the data is stored directly in the main memory, the Remote Dic­tion­ary Server requires sig­ni­fic­antly more main memory compared to other databases.

Instead of main­tain­ing sta­tion­ary databases, more and more companies are switching to cloud solutions. The ad­vant­ages are obvious: instead of a cost-intensive and power-hungry server on site, the company’s own data is out­sourced.

In addition to complete re­lo­ca­tion to the private or public cloud, there are also hybrid models that leave part of the data in-house in addition to the cloud. This can be a smart approach, es­pe­cially for par­tic­u­larly large data sets. The costs incurred can usually be estimated well and are not subject to strong fluc­tu­ations. There is no need to purchase or update expensive hardware or software. Linking different sites is also easier with a cloud model.

All of these open source databases are also suitable for full or hybrid cloud de­ploy­ment. If you opt for a cloud solution, you are probably also in­ter­ested in highly scalable databases. At the same time, you want fast response times, since the con­nec­tion to the cloud can cause slight latencies anyway. This is where Apache Cassandra and Redis come into play, as these two database systems are both highly scalable and impress with their great per­form­ance.