SQL vs. NoSQL: how to know when to use which

With similar sounding names, it’s easy to get SQL and NoSQL mixed up, and find yourself lost in the array of differences and comparison articles. Here’s your one stop for all things SQL and NoSQL — the good, the bad, and the differences between the two.

What is a SQL database?

SQL is a data structure and its acronym stands for “Structured Query Language”. It’s a programming language that has been used to manage data since the 1970s.

It’s known for its relational data structure, where data is kept in rows and tables that are linked together and speak to each other when executing queries. SQL is set apart by its programming language, which has a predefined schema for defining and manipulating data.

There are lots of different SQL databases for you to choose from. MySQL, Oracle, PostgreSQL, and Microsoft SQL Server are among the most popular. You’ll find that almost every big tech company uses SQL, from Netflix to Airbnb to Uber. Even web giants such as Google, Amazon, and Facebook use SQL to interact with their data.

What makes SQL cool

What is SQL good for? SQL is crazy popular. Here are some of the reasons why it’s so loved:

• Good for multi-row transactions
• Great for executing complex queries
• Plenty of community support
• Best for assessing data integrity
• Table-based for clean organization
• Vertically scalable — can increase the load on a single server by adding more memory
• Supports ACID*

*What is ACID in SQL?

Atomicity: all transactions must either succeed or fail completely

Consistency: at each step, the database follows invariants, which are rules that prevent corruption

Isolation: prevents concurrent transactions from affecting each other

Durability: makes transactions final

What makes SQL suck

But, as great as it is, SQL can be a pain — namely, it’s very restrictive because you have to use predefined schemas on the data before you even start using the data. Here are some other things we’re frustrated by when it comes to SQL:

• The SQL language is large and complex and can be hard to understand
• Inconsistent in syntax
• Doesn’t integrate well with application languages
• Tough to compose because of poor orthogonality (small set of primitive constructs that can only be combined in a few different ways)

While it has its frustrations, SQL is still really amazing tech. Now, let’s see what’s going on with NoSQL.

What is a NoSQL database?

In contrast to SQL, NoSQL is a non-relational data structure that’s set apart by its dynamic schemas for unstructured data. Rather than keeping data in tables, NoSQL uses documents, key-values, graphs, or wide-column stores.

There are plenty of popular NoSQL databases to choose from, like MongoDB, which is a favourite of ours. We also love BigTable, Redis, RavenDB Cassandra, HBase, Neo4j, and CouchDB.

Since NoSQL is awesome for large volumes of data that aren’t suited to a relational database, it’s used by lots of different companies that need to deal with extensive datasets, like Google, Amazon, and Netflix.

What makes NoSQL cool

What is NoSQL good for? Well, being able to manipulate complex data sets is pretty rad. Here are some other awesome features.

• Good for unstructured data (documents, JSON)
• Each document can have its own unique structure
• Syntax can vary between documents
• You can add fields as you go
• Horizontally scalable — sharding adds more servers to carry the load, which is better for larger and frequently changing data sets
• Supports BASE*

*What is BASE?

Basically Available: ensures availability of data by spreading and replicating it across the nodes of the database cluster

Soft State: rejecting the concept of a database that enforces its own consistency, this delegates the responsibility of making data consistent to developers

Eventually Consistent: just because this structure doesn’t enforce consistency doesn’t mean that it doesn’t achieve it

What makes NoSQL suck

Sounds pretty great, right? Still, NoSQL has its limitations:

• Less community support than SQL
• Compatibility issues with SQL
• Not standardized, so it’s hard to know that you’re doing things right
• Lack of cross-platform support
• Poor management tools
• Less data integrity
• Doesn’t support ACID*

*see previous

SQL vs. NoSQL comparison

Still dizzy with all the details? No sweat. Here’s your quick breakdown.

So… here’s when to use SQL vs. noSQL

Both are great data structures, but there are key differences between the two that make them more suited to different kinds of data sets.

NoSQL is great for data that is hierarchical or uses graphs, and in particular for large data sets that change a lot. It’s why you’ll see NoSQL is frequently used by businesses that are growing extremely fast but may not have a schema for their data.

In contrast, SQL is better for data that is well-represented by a table, and smaller data sets that don’t change much. As well, if there’s a need for consistency and security in data, SQL is your new best friend.

If you’re wondering when to use SQL vs NoSQL, consider your data set first. The better you understand the workload requirements of what you need the data for, the easier it is to find the right data structure to manage your workload. Often, companies will use both SQL and NoSQL for different types of data, so knowing both is an asset (and will keep you high in demand!), and will step up your coding game no matter what you’re using on the regular.

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