Choosing a Database

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Database vs Spreadsheet

A database allows multiple users to maintain, update, and edit stored information quickly, securely, and efficiently. That makes a database useful for a host of real-life cases such as keeping track of corporate accounting records, storing huge amounts of data from a network of IoT devices, tracking a company’s inventory systems, or building a web application.

Databases are designed for large datasets and high-performance operations, even with millions of records. The databases scale as the data grows, so they do not experience performance issues over time.

A spreadsheet is a single user software that stores data in cells. Spreadsheets are easy to use and can be set up quickly. Best for small to medium datasets; performance degrades with large data volumes.

Here are some considerations when choosing the right database:

Databases are essential for storing, maintaining, updating, editing, and accessing business information.
The two main categories of databases are SQL-based and NoSQL-based.
Oracle, MySQL, Microsoft SQL Server, PostgreSQL, and MongoDB are all popular business database solutions.
A full understanding of your business use case for storing and editing data can help you choose the right database option.
There are different types of modern databases available, each with a distinct set of advantages and disadvantages.

SQL-Based vs NoSQL-Based

Before diving into the most popular modern database options, it’s important to understand the difference between a relational database management system (SQL database) and a non-relational database management system (NoSQL database).

For most of the last 40 years, businesses relied on relational database management systems (RDBMSs) that used the programming language SQL.

However, NoSQL-based non-relational database management systems are becoming more popular — particularly because data scientists want to expose their machine learning business analytics tools to more unstructured data.

Relational Database Management Systems (SQL-Based)

SQL is a database management language that offers a highly organised and structured approach to information management. Similar to the way a phone book has different categories of information (name, number, address, etc.) for each line of data, relational databases apply strict, categorical parameters that allow database users to easily organise, access, and maintain information within those parameters.

The primary reasons why SQL-based RDBMSs continue to dominate are:

They are highly stable and reliable.
They adhere to a standard that integrates seamlessly with popular software stacks like LAMP.
We’ve been using them for more than 40 years.

Non-Relational Database Systems (NoSQL-Based)

Non-relational databases let you organize information in a looser fashion — kind of like dropping the information in different file folders. This is important for two reasons:

You can store unstructured information and expose it to powerful business intelligence systems that will analyze it with AI algorithms.
You can store unstructured data that you plan to structure later.

Non-relational databases also work with NoSQL formats like JSON, essential for web-based applications that let websites update “live” without needing to refresh the page.

Some non-relational DBMS advantages are:

Excellent for handling “big data” analytics: NoSQL databases remove the bottleneck of needing to categorize and apply strict structures to massive amounts of information. NoSQL databases like HBase, Cassandra, and CouchDB support the speed and efficiency of server operations while offering the capacity to work with large amounts of data.
No limits on types of data you can store: NoSQL databases give you unlimited freedom to store diverse types of data in the same place. This offers the flexibility to add new and different types of data to your database at any time.
Easier to scale: NoSQL databases are easier to scale. They’re designed to be fragmented across multiple data centers without much difficulty.

Some non-relational DBMS disadvantages are:

More difficult to find support: It can be more difficult to find experienced users when you need to troubleshoot.
Lack of tools: Since the system is relatively new compared to SQL-based RDBMS solutions, there aren’t as many tools to assist with performance testing and analysis.
Compatibility and standardisation challenges: Newer NoSQL database systems also lack the high degree of compatibility and standardisation offered by SQL-based alternatives.

Oracle Database

Oracle has provided high-quality database solutions since the 1970s. The most recent version of Oracle Database was designed to integrate with cloud-based systems, and it allows you to manage massive databases with billions of records. Oracle offers SQL and NoSQL database solutions.

Oracle database advantages:

The most advanced technology: Oracle is known for being on the leading edge of database technology. They have a long-standing reputation for bringing quality, features, and innovations to their customer base.
A wide range of solutions: Oracle offers a massive suite of tools and solutions that can address most information challenges you encounter.

Oracle database disadvantages:

An expensive solution: Oracle tends to be a high-cost solution that smaller, non-enterprise-level organizations might not be able to afford.
System upgrades might be required: Your current system specifications might not be enough to implement Oracle. Many businesses have to upgrade their hardware before using Oracle solutions.

Best use case for Oracle: If you’re a large organization that needs to manage a massive amount of data, Oracle could be the ideal choice.

MySQL

MySQL is a free (which is why we’ll be using it), open-source RDBMS solution that Oracle owns and manages. Even though it’s freeware, MySQL benefits from frequent security and feature updates. Large enterprises can upgrade to paid versions of MySQL to benefit from additional features and user support. Although MySQL didn’t support NoSQL in the past, since Version 8, it provides NoSQL support to compete with other solutions like PostgreSQL. Read more about the differences between MySQL and PostgreSQL here.

MySQL advantages:

It’s free: As an open-source RDBMS solution, MySQL is free to use in any way you want.
Highly compatible with other systems: MySQL has a reputation for being compatible with many other database systems.

MySQL disadvantages:

Missing features common to other RDBMSs: Because MySQL prioritizes speed and agility over features, you might find that it’s missing some of the standard features found in other solutions.
Challenges in getting quality support: The free version of MySQL does not come with on-demand support. However, MySQL does have an active volunteer community, user forums, and plenty of useful documentation.

Best use case for MySQL: MySQL is a particularly valuable RDBMS solution for businesses that need a solution with enterprise-level capabilities but are operating under strict budget constraints. It’s an extremely powerful and reliable modern RDBMS with a free tier.

Microsoft SQL Server

Microsoft SQL Server is a database engine that’s compatible with on-site and cloud-based servers. Moreover, there is a Windows and a Linux version of Microsoft SQL. Microsoft also offers temporal data support. The feature is useful for querying historical data that may have changed state.

Microsoft SQL Server supports dynamic data masking, which boosts security by masking sensitive information from non-privileged users.

Microsoft SQL Server advantages:

Mobile: This database engine allows you to access dashboard graphics and visuals via mobile devices.
Integrates with Microsoft products: Companies that rely heavily on Microsoft products will enjoy the way SQL Server integrates easily with these applications.
Fast: Microsoft SQL Server has built a reputation around being fast and stable.

Microsoft SQL Server disadvantages:

Expensive: It’s over USD$14,000 for one enterprise-level license per core. There are scaled-down licensing options for approximately $3,700 and $900, and a free version you can use to test the platform.

Best use case for Microsoft SQL Server: If you’re an enterprise-level corporation that relies heavily on Microsoft products, the speed, agility, and reliability of Microsoft SQL Server could be an excellent choice.

PostgreSQL

PostgreSQL is an open-source, free database engine with unlimited scaling capabilities. PostgreSQL supports both relational and non-relational data formats.

As a highly trusted DBMS that has been around since the early 1990s, PostgreSQL has a devoted user base and has won the prestigious Database of the Year Award, twice.

An interesting feature of PostgreSQL is its history of working with both structured (SQL) and unstructured (NoSQL) data. PostgreSQL has a catalog-driven approach, which makes it highly extensible. It doesn’t simply store information to identify tables and columns. It allows you to define data types, index types, and functional languages. It’s also compatible with most operating systems, including Linux platforms, and it integrates well with data from a wide variety of databases. PostgreSQL also works with, both, on-site servers and cloud-based servers.

Even though it’s a nonprofit, free database system, a large network of devoted followers and volunteers offer free support to users and regularly update the system.

Best use case for PostgreSQL: Since PostgreSQL is completely free and scalable, this is an excellent solution for companies of any size. More importantly, if you can benefit from a DBMS with native JSON support, PostgreSQL is for you.

MongoDB

MongoDB is a free, open-source database engine built especially for applications that use unstructured data. Because most DBMSs were built for structured data — even if add-ons allow them to handle non-relational data now — MongoDB excels where other DBMSs fail. MongoDB works with structured data too, but since this database engine wasn’t designed for relational data, performance slowdowns are likely.

MongoDB connects non-relational databases with applications by using a wide variety of drivers (based on the programming language of the application). The most recent versions of MongoDB include pluggable storage engines. Upgraded text search features are also available, along with partial indexing features, which can help with performance.

MongoDB advantages:

NoSQL support: This DBMS was specifically made to support JSON and NoSQL data.
Highly flexible: Since MongoDB stores and manages any kind of information, developers face fewer restrictions when incorporating data into a MongoDB database.
Great for applications including web-based apps: MongoDB has become a popular DBMS for web-based applications.

MongoDB disadvantages:

No SQL querying: MongoDB will not accept SQL queries. You can use additional tools to translate your SQL queries to work with this database engine. However, the workaround can be inconvenient.
Difficult to set up: MongoDB takes time and more experience to set up properly than other solutions.
Lack of security: The native settings on MongoDB don’t tend to be very secure. Additional steps will be required to secure this database.