What alternatives to SQL are there?

Relational databases can be a good solution for structured data. However, if you need more flexible storage, the NoSQL approach is usually a better option. We’ll explain which alternatives to SQL are best.

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 summarized 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

If you’d like to find out more about the similarities and differences between SQL and MongoDB, we recommend reading the comprehensive article about the two databases in our Digital Guide.

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

You’ll find more details about the advantages and special features of Apache Cassandra in our Digital Guide.

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 synchronization, 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 synchronization
• 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