MySQL vs Oracle: core differences and similarities

Given an overwhelming variety of databases, choosing the best fit for your application is not a trivial task. Different aspects of your project have to be considered to find the database that perfectly matches its requirements. 

To assist you in making an informed decision about it, we’ve decided to create a special blog series, in which we’re going to overview the most popular modern databases and warehouses that withstood the test of time and are most appreciated by the community of developers and database administrators.

This time we'll focus on the core differences between MySQL and Oracle and figure out what these relational databases have in common. 

Let's begin by briefly introducing both databases.

MySQL

MySQL, released in 1995, is a relational database management system that was one of the first open-source solutions in the market. According to the latest Stack Overflow Survey 2019 results, MySQL holds the position of the most commonly used database for the third year in a row, edging ahead of PostgreSQL and Microsoft SQL Server. It also has the largest market share. 

Thanks to being perfectly optimized for the web, it’s the first database choice for web-based applications. Together with Apache and PHP, MySQL forms one of the most commonly used tech stacks. It's loved for its ease of use and excellent security, availability, cost-effective replication, and increased reliability features.

Oracle

Oracle database, released in 1977, is a relational database management system (RDBMS) developed and maintained by Oracle Corporation. Starting as a Silicon Valley’s startup, nowadays Oracle DB is one of the most trustworthy database engines. Moreover, Oracle Corporation always stays ahead of the technology curve, delivering innovations in the field of data integration tools. This cannot but affect the pace of development of the Oracle DB itself.

According to the Stack Overflow Survey 2019 results, the developers' attitude to Oracle DB can be described as controversial - along with Couchbase, it's one of the most dreaded databases. 

However, there are a lot of aspects to love about Oracle DB. It’s the first database developed for grid computing which enables IT systems to deliver the high value of service and better flexibility at less cost.

What MySQL and Oracle share in common

The core similarity of Oracle DB and MySQL is that they are both relational and support SQL. The languages of implementation are the same: C and C++. Furthermore, both are among the top 10 databases used by developers around the globe.

Now let’s figure out the differences between these two databases.

License model

MySQL. Despite having a free and open-source development model, after getting acquired by Oracle Corporation, MySQL offered different commercial license versions with premium support services for enterprises.

When distributing an application that uses MySQL, its code must be available in the open-source sense.  If making your code available under the GPL is not an option for you, you can select one of the commercial licenses.

Oracle. In contrast to MySQL, Oracle DB is a completely proprietary database. The only licensing model that allows using Oracle DB for free is Oracle Express Edition. But note that it’s limited to one database. Other models to consider depend on the number of users, the capacity of servers, and other features.

Performance and scalability

As with any database, the scalability of MySQL heavily depends on various factors - the architecture, operating system, hardware, database's version and configuration, indexing, and its schema design. But there are plenty of features of MySQL that you can benefit from to deliver the faster performance of your database application:

• InnoDB - a storage engine that is designed to ensure high performance and scalability and handle transactional applications.
• MySQL Replication.
• Rapid connection handling.
• Memory tables for fast time of response.
• Auto-sharding.
• Full support of partitioning.

Oracle DB is designed to leverage large-scale deployments out-of-the-box. It's enriched with the performance-related features that make execution, storage, availability, and management fully scalable.

Large enterprises choose Oracle DB for its scalable architecture that can be divided into logical and physical parts. It means that the logical data structure allows storing data and interacting with the database without requiring to know where it’s physically stored. The typical use case of Oracle DB involves online transaction processing and data warehousing.

For more details on how Oracle DB functionality helps to scale up to thousands of processors and handle large amounts of data, we recommend checking out this white paper.

Data partitioning methods

Partitioning is a process that defines how the separate tables are broken down in shares and stored in different locations. There are two partitioning types: horizontal and vertical. Horizontal partitioning means rows of a table can be assigned to different physical locations. Accordingly, vertical partitioning means different columns of a table are assigned to different physical partitions. 

MySQL supports horizontal partitioning only. There’s one important restriction to remember – partitions of the same table must use the same storage engine (InnoDB or NDB). Methods of the data partitioning in MySQL include range– and hash-based partitioning. The benefit of partitioning by hash is that the data can be written to these partitions more concurrently.

Oracle supports both vertical and horizontal partitioning. It also offers a lot of partitioning methods: by range, list, hash, multi-column range, interval, composite, reference, virtual column-based, and interval reference. All these methods can be used with any application.

Indexes types

MySQL lets you use B-Tree, B+Tree, and hash data structures for your indexes. The B-tree is the basic data structure for most engines of MySQL. However, if you have spatial indexes, the database engine will use R-trees that are better at indexing multidimensional data.

Oracle DB offers a much wider choice of indexes types: indexes that use B*-trees, reverse key indexes, bitmap indexes, function-based indexes, invisible indexes, storage indexes, partitioned indexes, and more. By default, Oracle uses the B*-tree data structure for indexes.

Clustering & replication

Replication is an important process that allows having multiple copies of the same data copied from 'master' to 'slave' databases. It has to be done automatically to ensure the high availability of data.

MySQL supports one-way asynchronous master-slave replication by default. Synchronous, semi-synchronous and delayed replication types are supported likewise. In MySQL, you can replicate all databases, selected databases or selected tables within a certain database.

Oracle provides a possibility to make up a distributed database system as well. 

It supports several types of replication environments: multimaster, snapshot, and multimaster-snapshot hybrid replication types. The most common way to implement replication is asynchronous but synchronous and procedural replication types are supported, too.

Operating systems

Both MySQL and Oracle are about flexibility of choice - you can run them on the majority of operating systems, including Oracle/RedHat Enterprise Linux, Fedora Linux, Ubuntu Linux, Debian Linux, SuSE Linux, Oracle Solaris, Microsoft Windows, Apple macOS, FreeBSD, and more.

Data integrity

Traditionally, MySQL shifted the responsibility of validating incoming data to the front-end of the application. But since MySQL 5.0, the data integrity is provided at the database engine layer, meaning the incoming data is validated and rejected if any part of it has the incorrect data type that breaks the rules of data integrity.

Oracle DB also respects the principle that data integrity has always be maintained. To prevent the entry of invalid data into tables, you can use multiple techniques: to reinforce business rules via triggered stored database procedures, the code of a database app, or Oracle Database integrity constraints.

Memory-only

Both databases support an ability to store different data structures in memory only. 

Roles

In MySQL, each privilege must be granted separately. In Oracle, you can create and assign roles that incorporate different privileges together. 

Character types

Both MySQL and Oracle support CHAR and VARCHAR. But Oracle supports also NCHAR, NVARCHAR2, and VARCHAR2, which can store Unicode characters.

Column default value

A radical difference between two databases lies in the way they treat default values. In MySQL, if a column can’t be NULL, the default value is generated for that column. In Oracle, when inserting a new record, the columns that can’t be NULL have to be provided with data.

Compatibility with programming languages 

The lists of supported programming languages for both databases are indeed exhaustive. 

Both MySQL and Oracle support C, C#, C++, Delphi, Eiffel, Erlang, Haskell, Java, Python, Ruby, Objective-C, OCaml, JavaScript, Perl, PHP, and a lot more.

Syntax of queries

Commands for creating tables in MySQL and Oracle are almost identical. There is a minimal learning curve when transferring from Oracle DB to MySQL or vice versa. 

Which companies are using MySQL?

According to information on the official website, MySQL is actively used by Facebook, eBay, Netflix, YouTube, Cisco Systems, IBM, and a lot of other giants that lead the technology industry.

Which companies are using Oracle?

Among the companies and organizations that successfully use Oracle DB in their products are Sony, Vodafone, Evotech Solution, Cisco Systems, Inc., Western Digital and many others.

So, which one is better - MySQL or Oracle? The answer depends on the requirements and structure of your project. And we do hope that soon after reading this blog post you'll get a clear understanding of both databases specifics and pick the one that suits your project and organization best.

Visualizing MySQL and Oracle data

Whichever database you use, you can make sense of its data using web-based reporting solutions. This is where Flexmonster comes in handy - a lightweight JavaScript library that tackles the most sophisticated reporting challenges. Without a hitch, you can connect the pivot table to an Oracle database or a MySQL database and start your data analysis in minutes. Another feature you may like is how smoothly Flexmonster can be integrated with any front-end technology.