7 Types of Databases That Every Backend Developer Should Know

Published by Piotr Blachnio on

7 Types of Database That Every Backend Developer Should Know

Have you always wondered which database you should choose for your next project? Should you pick relational, non-relational, or something else? Each database type works best for its specific use case. You should definitely consider it before making the final decision. This article will give you some insights into different types of databases, their proscons, and use cases.

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What about the backend development? Do you want to become a backend developer and start your career working on the server-side? Here is a Step-by-Step Tutorial for you.

1. Relational databases

MySQL relational database homepage

Let’s start with the most common ones – relational databases. They were invented over 50 years ago, and they’re still one of the most popular databases nowadays. Relational databases require us to have a predefined schema in order to organize the data into tables, columns, and rows. We use the SQL language to perform operations such as creating, updating, deleting, and reading.

Use cases

  • Applications with well-structured and consistent data
  • Applications with data containing many relationships
  • Social networking websites
  • Banking
  • Stock trading apps

Advantages

  • ACID transactions
  • Data consistency
  • Maturity

Disadvantages

  • Hard to scale
  • Limited amount of complex data types (e.g., drawings)
  • Changing the predefined schema can be very time-consuming

Popular databases

Learning Resources

2. Document-oriented databases

MongoDB document-oriented type of database homepage

Moving on to the next type – document-oriented databases. They store entries in the form of documents (e.g., JSON, BSON, XML). They don’t require a predefined schema, and the data doesn’t have to be well-structured. Document-oriented databases are commonly used in many modern applications, and a lot of people consider them easier to work with than relational databases.

Use cases

  • Applications with unstructured and semi-structured data
  • Mobile applications
  • IoT
  • Content Management Systems

Advantages

  • Easy to scale
  • Schemaless
  • High performance

Disadvantages

  • No ACID transactions (in most cases)
  • Lack of a query language (e.g., SQL)
  • Not that mature yet

Popular databases

Learning Resources

3. Key-value databases

Redis key-value types of database homepage

Key-value databases are used to store data in a way that each key is unique and holds a specific value. The whole structure of the data is similar to a hash table or dictionary. Thanks to storing data inside machine memory, key-value databases are incredibly fast. On the other hand, such architecture limits the amount of data that you can keep.

Use cases

  • Caching
  • Session storage
  • URL Shorteners

Advantages

  • Extremely fast
  • Flexible to work with

Disadvantages

  • Limited amount of data that you can store
  • Bad for complex queries
  • Scaling can be costly

Popular databases

Learning Resources

4. Wide-column databases

CassandraDB wide-column database

The next type on our list – wide-column databases. They are designed to store a massive amount of data in a scalable way. Wide-column databases don’t follow the relational model, and they are not optimized for joins operations. What’s interesting, they can are called two-dimensional key-value stores.

Use cases

  • Applications with frequent writes and occasional reads.
  • Time series data
  • IoT
  • Big, large scale applications

Advantages

  • Scalable
  • Superfast writes
  • Easy to manage large data sets

Disadvantages

  • Slow reads, updates, and deletes
  • Effective indexing can be hard to design

Popular databases

Learning Resources

5. Search-engine databases

Elasticsearch database homepage

Search-engine databases work very similarly to document-oriented databases. The main difference is that a search-engine database analyzes all the text in the document and creates an index of searchable terms. They are very popular when it comes to filtering and finding data in large data sets. Moreover, search-engine databases store unstructured data without having a predefined schema.

Use cases

  • Search engines
  • Typeahead search box

Advantages

  • Very scalable
  • Extremely fast searching
  • Flexible schema

Disadvantages

  • Not efficient when it comes to reading and writing data outside searching
  • Not very secure
  • No transactions support

Popular databases

Learning Resources

6. Graph databases

Neo4j graph types of database showing homepage

Graph databases are NoSQL databases that use graphs, nodes, and edges to represent the data. All the information is stored inside nodes, and it uses edges to make connections between them. With such architecture, it’s very easy and straightforward to visualize all the data inside our storage.

Use cases

  • Social networking applications
  • Fraud detection systems
  • Geological routing and visualization

Advantages

  • Operation speed is based on relationships and not on the amount of data
  • Allow a compact and clear representation of data
  • Have flexible and agile structures

Disadvantages

  • Not suitable for simple use cases
  • Bad performance of aggregate queries
  • Difficult to scale

Popular databases

Learning Resources

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7. Multi-model databases

FaunaDB representing multi-model databases showing website homepage

Multi-model databases are about implementing various data storage technologies to handle different use cases. Let’s take a look at the most popular one – FaunaDB. If you’re a frontend developer or you just don’t want to think about modeling, data replication, sharding, schemas, etc. – this database might be the right choice for you. With FaunaDB, you describe how you want to get the data using GraphQL or FQL. Under the hood, FaunaDB takes advantage of other database types and picks the best choice for your specific use case.

Use cases

  • Real-time consumer applications
  • Financial services
  • E-commerce

Advantages

  • Extremely fast
  • Takes advantage of other types of databases
  • Offers ACID transactions

Disadvantages

  • Limited support
  • Relatively young technology

Popular databases

Learning Resources

7 Types of Databases – Conclusion

There are many interesting types of databases that you should consider for your next project. Each of them has its own pros and cons, as well, use cases. You should think about your specific project and decide which type fits best into your case. Sometimes, you’ll need to use more than one database type. You can also take a look at how big-tech companies approach this problem. How can they handle such a significant amount of traffic? If you want to learn more about it, here are great articles describing their architecture.

Remember that our industry changes very rapidly. Some technologies are being replaced by new ones every week. Therefore, it’s crucial for us to never stop learning and improving ourselves. So keep this in mind and create some amazing projects that will move you to the next level!

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