What al­tern­at­ives to SQL are there?

Re­la­tion­al databases are still a great solution for struc­tured data, but when more flexible storage is needed, the NoSQL approach is usually a better fit. We’ll explain which SQL al­tern­at­ives might be par­tic­u­larly well-suited for your needs.

What is SQL and what al­tern­at­ives are there?

For several decades, the re­la­tion­al approach was the standard for all databases. Data was, and in some cases, still is stored and managed in tables. Database man­age­ment systems such as MySQL and Post­gr­eSQL rely on the common query language SQL (Struc­tured Query Language), which offer users numerous ad­vant­ages. The SQL approach is user-friendly and clear and the databases are secure and scalable. Many SQL databases are also based on ACID prop­er­ties (Atomicity, Con­sist­ency, Isolation, Dur­ab­il­ity), guar­an­tee­ing the reliable transfer of data. If you need to structure data in tabular form, the ad­vant­ages of SQL make a strong case for the database.

Many large companies and platforms still partially rely on a re­la­tion­al solution. But when it comes to storing semi-struc­tured and un­struc­tured data, tables either aren’t ideal or simply aren’t possible. The in­creas­ing need for larger, het­ero­gen­eous data volumes has caused users to rethink their approach. NoSQL databases (Not only SQL) store data in the form of documents, making them often more flexible. However, you don’t have to com­pletely do away with your re­la­tion­al database. You can also combine it with a document-oriented solution. However, if you’re looking for an SQL al­tern­at­ive, and not just an add-on, a NoSQL database is re­com­men­ded.

MongoDB—Ideal for large amounts of data

The NoSQL approach has numerous ad­vant­ages. A prime example of a great NoSQL database is MongoDB. This SQL al­tern­at­ive has been available since 2009 and owes its name to the word ‘huMONGOus’. So it shouldn’t come as a surprise that MongoDB is primarily designed for large amounts of data. The database can be scaled ho­ri­zont­ally, which makes it ideal for in­creas­ing data volumes and is one of the reasons it’s popular among small and large companies alike. MongoDB stores data in binary JSON documents, which are then sum­mar­ised into col­lec­tions. The stored data can be struc­tured, semi-struc­tured or un­struc­tured, making MongoDB one of the most flexible solutions out there.

The ad­vant­ages of MongoDB at a glance

• Limitless ho­ri­zont­al scalab­il­ity
• Almost all data types can be saved and managed
• High avail­ab­il­ity and re­li­ab­il­ity due to storage on multiple nodes
• User-friendly
• Rep­lic­a­tions possible
• Com­pat­ible with numerous other systems, languages and platforms
• Large and dedicated community and extensive doc­u­ment­a­tion
• Can be combined with SQL

MariaDB—The free and powerful NoSQL al­tern­at­ive

MariaDB isn’t strictly a tra­di­tion­al NoSQL database, but rather an open-source re­la­tion­al solution and a direct fork of MySQL. However, it offers many modern ex­ten­sions that make it suitable for various projects. It’s par­tic­u­larly in­ter­est­ing for de­velopers who want to work with re­la­tion­al struc­tures while seeking more flex­ib­il­ity and in­de­pend­ence from large cor­por­a­tions. MariaDB is already included by default in many dis­tri­bu­tions and, thanks to a variety of storage engines, high per­form­ance, and scalab­il­ity, it’s also a great fit for complex ap­plic­a­tions. Hybrid scenarios are also possible: MariaDB supports JSON functions and can partially work with document-oriented data—making it closer to modern NoSQL solutions.

The ad­vant­ages of MariaDB at a glance

• Open-source and in­de­pend­ent from large cor­por­a­tions
• Fully com­pat­ible with MySQL
• High per­form­ance and stability
• Supports complex queries and trans­ac­tions
• Flexible storage with various storage engines
• Advanced JSON functions
• Active community and regular updates
• Ideal for hybrid database ar­chi­tec­tures

Apache Cassandra—The column-oriented NoSQL database

Apache Cassandra follows a similar approach. However, this NoSQL database is column-oriented and uses CQL, a query language similar to SQL. This makes things a little easier for users trans­ition­ing from a re­la­tion­al method. Apache Cassandra scores points for its capacity to store large amounts of data. The open-source solution is ho­ri­zont­ally and ver­tic­ally scalable and also stores data on multiple nodes as key-value pairs. Companies and platforms like Apple and Netflix use Apache Cassandra for their data streams. The system offers high speeds and is con­sidered to be fail-safe, which makes it a great al­tern­at­ive to SQL.

The ad­vant­ages of Apache Cassandra at a glance

• Open source
• Ho­ri­zont­ally and ver­tic­ally scalable
• CQL is similar to SQL
• Storage in columns
• Strong per­form­ance
• High re­li­ab­il­ity and avail­ab­il­ity of data
• Rep­lic­a­tions possible
• High fault tolerance
• Committed community

DynamoDB—The fully managed al­tern­at­ive to SQL

DynamoDB, on the other hand, works com­pletely dif­fer­ently. The solution from the AWS ecosystem (Amazon Web Services) also follows the NoSQL approach but has a com­pletely different focus. Where other databases guarantee flex­ib­il­ity through different data types and a high level of com­pat­ib­il­ity, DynamoDB focuses on user-friend­li­ness. It also offers ex­ceed­ingly high levels of security. The system is embedded in the AWS ecosystem and cannot be separated from it. This server­less option comes fully managed. That means users don’t have to worry about security updates or upgrades but can im­me­di­ately get working with the database instead. Payment is based on the user’s in­di­vidu­al re­quire­ments and the resources they use.

The ad­vant­ages of DynamoDB at a glance

• Com­pletely managed
• Secure solution
• High avail­ab­il­ity
• Un­res­tric­ted scaling as required
• High read and write speed
• Embedding in the AWS ecosystem
• Always up to date

Firebase—The de­vel­op­ment platform from Google

Google’s SQL al­tern­at­ive, Firebase, has been extremely suc­cess­ful. Firebase is a complete de­vel­op­ment platform that consists of a total of 18 services (some of which are subject to a fee). This includes a database that is capable of real-time syn­chron­isa­tion, making it perfect for mobile and web ap­plic­a­tions. Gaming apps, chat programs and social networks benefit par­tic­u­larly well from this solution. Firebase stores data in JSON documents and is very secure. It offers close links to various Google services. This con­nec­tion to the Google ecosystem, however, limits migration options. Firebase is still worth con­sid­er­ing though if you are looking for a powerful database for de­vel­op­ment.

The ad­vant­ages of Firebase at a glance

• Part of a complete de­vel­op­ment platform
• Ideal for mobile and web ap­plic­a­tions
• Clever in­teg­ra­tion of Google services
• High avail­ab­il­ity and re­li­ab­il­ity
• Real-time syn­chron­isa­tion
• Strong cloud con­nec­tion
• Good support

Redis—The best choice for fast response times

If you want to store and retrieve large, struc­tured amounts of data there are lots of good SQL solutions. However, if you have a project that requires par­tic­u­larly high speeds, an in-memory database such as Redis might be a better option. Redis sorts data into key-value pairs and stores it directly in the main memory. This is what enables its response times of less than one mil­li­second. Although this means large volumes of data use up a huge amount of storage space, the free solution offers out­stand­ing results for caches, real-time analyses, games and streaming. Redis isn’t just a good al­tern­at­ive to SQL, it can also be used in com­bin­a­tion with a re­la­tion­al database.

The ad­vant­ages of Redis at a glance

• Open source
• High speed due to storage in the working memory
• Ho­ri­zont­al and vertical scaling
• Very user-friendly
• High com­pat­ib­il­ity with several pro­gram­ming languages
• Can be used with SQL solutions
• High avail­ab­il­ity