The relational data model, which organizes data in tables of rows and columns, predominates in database management tools. Today there are other data models, including NoSQL and NewSQL, but relational database management systems (RDBMSs) remain dominant for storing and managing data worldwide.
This article compares and contrasts three of the most widely implemented open-source RDBMSs: SQLite, MySQL, and PostgreSQL. Specifically, it will explore the data types that each RDBMS uses, their advantages and disadvantages, and situations where they are best optimized.
Databases are logically modelled clusters of information, or data. A database management system (DBMS), on the other hand, is a computer program that interacts with a database. A DBMS allows you to control access to a database, write data, run queries, and perform any other tasks related to database management.
Although database management systems are often referred to as “databases,” the two terms are not interchangeable. A database can be any collection of data, not just one stored on a computer. In contrast, a DBMS specifically refers to the software that allows you to interact with a database.
All database management systems have an underlying model that structures how data is stored and accessed. A relational database management system is a DBMS that employs the relational data model. In this relational model, data is organized into tables. Tables, in the context of RDBMSs, are more formally referred to as relations. A relation is a set of tuples, which are the rows in a table, and each tuple shares a set of attributes, which are the columns in a table:
Most relational databases use structured query language (SQL) to manage and query data. However, many RDBMSs use their own particular dialect of SQL, which may have certain limitations or extensions. These extensions typically include extra features that allow users to perform more complex operations than they otherwise could with standard SQL.
Note: The term “standard SQL” comes up several times throughout this guide. SQL standards are jointly maintained by the American National Standards Institute (ANSI), the International Organization for Standardization (ISO), and the International Electrotechnical Commission (IEC). Whenever this article mentions “standard SQL” or “the SQL standard,” it’s referring to the current version of the SQL standard published by these bodies.
It should be noted that the full SQL standard is large and complex: full core SQL:2011 compliance requires 179 features. Because of this, most RDBMSs don’t support the entire standard, although some do come closer to full compliance than others.
Each column is assigned a data type which dictates what kind of entries are allowed in that column. Different RDBMSs implement different data types, which aren’t always directly interchangeable. Some common data types include dates, strings, integers, and Booleans.
Storing integers in a database is more nuanced than putting numbers in a table. Numeric data types can either be signed, meaning they can represent both positive and negative numbers, or unsigned, which means they can only represent positive numbers. For example, MySQL’s tinyint
data type can hold 8 bits of data, which equates to 256 possible values. The signed range of this data type is from -128 to 127, while the unsigned range is from 0 to 255.
Being able to control what data is allowed into a database is important. Sometimes, a database administrator will impose a constraint on a table to limit what values can be entered into it. A constraint typically applies to one particular column, but some constraints can also apply to an entire table. Here are some constraints that are commonly used in SQL:
UNIQUE
: Applying this constraint to a column ensures that no two entries in that column are identical.NOT NULL
: This constraint ensures that a column doesn’t have any NULL
entries.PRIMARY KEY
: A combination of UNIQUE
and NOT NULL
, the PRIMARY KEY
constraint ensures that no entry in the column is NULL
and that every entry is distinct.FOREIGN KEY
: A FOREIGN KEY
is a column in one table that refers to the PRIMARY KEY
of another table. This constraint is used to link two tables together. Entries to the FOREIGN KEY
column must already exist in the parent PRIMARY KEY
column for the write process to succeed.CHECK
: This constraint limits the range of values that can be entered into a column. For example, if your application is intended only for residents of Alaska, you could add a CHECK
constraint on a ZIP code column to only allow entries between 99501 and 99950.If you’d like to learn more about database management systems, check out our article on A Comparison of NoSQL Database Management Systems and Models.
Now that we’ve covered relational database management systems generally, let’s move onto the first of the three open-source relational databases this article will cover: SQLite.
SQLite is a self-contained, file-based, and fully open-source RDBMS known for its portability, reliability, and strong performance even in low-memory environments. Its transactions are ACID-compliant, even in cases where the system crashes or undergoes a power outage.
The SQLite project’s website describes it as a “serverless” database. Most relational database engines are implemented as a server process in which programs communicate with the host server through an interprocess communication that relays requests. In contrast, SQLite allows any process that accesses the database to read and write to the database disk file directly. This simplifies SQLite’s setup process, since it eliminates any need to configure a server process. Likewise, there’s no configuration necessary for programs that will use the SQLite database: all they need is access to the disk.
SQLite is free and open-source software, and no special license is required to use it. However, the project does offer several extensions — each for a one-time fee — that help with compression and encryption. Additionally, the project offers various commercial support packages, each for an annual fee.
SQLite allows a variety of data types, organized into the following storage classes:
Data Type | Explanation |
---|---|
null |
Includes any NULL values. |
integer |
Signed integers, stored in 1, 2, 3, 4, 6, or 8 bytes depending on the magnitude of the value. |
real |
Real numbers, or floating point values, stored as 8-byte floating point numbers. |
text |
Text strings stored using the database encoding, which can either be UTF-8, UTF-16BE or UTF-16LE. |
blob |
Any blob of data, with every blob stored exactly as it was input. |
In the context of SQLite, the terms “storage class” and “data type” are considered interchangeable. If you’d like to learn more about SQLite’s data types and SQLite type affinity, check out SQLite’s official documentation on the subject.
According to the DB-Engines Ranking, MySQL has been the most popular open-source RDBMS since the site began tracking database popularity in 2012. It is a feature-rich product that powers many of the world’s largest websites and applications, including Twitter, Facebook, Netflix, and Spotify. Getting started with MySQL is relatively straightforward, thanks in large part to its exhaustive documentation and large community of developers, as well as the abundance of MySQL-related resources online.
MySQL was designed for speed and reliability, at the expense of full adherence to standard SQL. The MySQL developers continually work towards closer adherence to standard SQL, but it still lags behind other SQL implementations. It does, however, come with various SQL modes and extensions that bring it closer to compliance.
Unlike applications using SQLite, applications using a MySQL database access it through a separate daemon process. Because the server process stands between the database and other applications, it allows for greater control over who has access to the database.
MySQL has inspired a wealth of third-party applications, tools, and integrated libraries that extend its functionality and help make it easier to work with. Some of the more widely-used of these third-party tools are phpMyAdmin, DBeaver, and HeidiSQL.
MySQL’s data types can be organized into three broad categories: numeric types, date and time types, and string types.
Numeric types:
Data Type | Explanation |
---|---|
tinyint |
A very small integer. The signed range for this numeric data type is -128 to 127, while the unsigned range is 0 to 255. |
smallint |
A small integer. The signed range for this numeric type is -32768 to 32767, while the unsigned range is 0 to 65535. |
mediumint |
A medium-sized integer. The signed range for this numeric data type is -8388608 to 8388607, while the unsigned range is 0 to 16777215. |
int or integer |
A normal-sized integer. The signed range for this numeric data type is -2147483648 to 2147483647, while the unsigned range is 0 to 4294967295. |
bigint |
A large integer. The signed range for this numeric data type is -9223372036854775808 to 9223372036854775807, while the unsigned range is 0 to 18446744073709551615. |
float |
A small (single-precision) floating-point number. |
double , double precision , or real |
A normal sized (double-precision) floating-point number. |
dec , decimal , fixed , or numeric |
A packed fixed-point number. The display length of entries for this data type is defined when the column is created, and every entry adheres to that length. |
bool or boolean |
A Boolean is a data type that only has two possible values, usually either true or false . |
bit |
A bit value type for which you can specify the number of bits per value, from 1 to 64. |
Date and time types:
Data Type | Explanation |
---|---|
date |
A date, represented as YYYY-MM-DD . |
datetime |
A timestamp showing the date and time, displayed as YYYY-MM-DD HH:MM:SS . |
timestamp |
A timestamp indicating the amount of time since the Unix epoch (00:00:00 on January 1, 1970). |
time |
A time of day, displayed as HH:MM:SS . |
year |
A year expressed in either a 2 or 4 digit format, with 4 digits being the default. |
String types:
Data Type | Explanation |
---|---|
char |
A fixed-length string; entries of this type are padded on the right with spaces to meet the specified length when stored. |
varchar |
A string of variable length. |
binary |
Similar to the char type, but a binary byte string of a specified length rather than a nonbinary character string. |
varbinary |
Similar to the varchar type, but a binary byte string of a variable length rather than a nonbinary character string. |
blob |
A binary string with a maximum length of 65535 (2^16 - 1) bytes of data. |
tinyblob |
A blob column with a maximum length of 255 (2^8 - 1) bytes of data. |
mediumblob |
A blob column with a maximum length of 16777215 (2^24 - 1) bytes of data. |
longblob |
A blob column with a maximum length of 4294967295 (2^32 - 1) bytes of data. |
text |
A string with a maximum length of 65535 (2^16 - 1) characters. |
tinytext |
A text column with a maximum length of 255 (2^8 - 1) characters. |
mediumtext |
A text column with a maximum length of 16777215 (2^24 - 1) characters. |
longtext |
A text column with a maximum length of 4294967295 (2^32 - 1) characters. |
enum |
An enumeration, which is a string object that takes a single value from a list of values that are declared when the table is created. |
set |
Similar to an enumeration, a string object that can have zero or more values, each of which must be chosen from a list of allowed values that are specified when the table is created. |
FULL JOIN
clauses.PostgreSQL, also known as Postgres, bills itself as “the most advanced open-source relational database in the world.” It was created with the goal of being highly extensible and standards compliant. PostgreSQL is an object-relational database, meaning that although it’s primarily a relational database it also includes features — like table inheritance and function overloading — that are more often associated with object databases.
Postgres is capable of efficiently handling multiple tasks at the same time, a characteristic known as concurrency. It achieves this without read locks thanks to its implementation of Multiversion Concurrency Control (MVCC), which ensures the atomicity, consistency, isolation, and durability of its transactions, also known as ACID compliance.
PostgreSQL isn’t as widely used as MySQL, but there are still a number of third-party tools and libraries designed to simplify working with with PostgreSQL, including pgAdmin and Postbird.
PostgreSQL supports numeric, string, and date and time data types like MySQL. In addition, it supports data types for geometric shapes, network addresses, bit strings, text searches, and JSON entries, as well as several idiosyncratic data types.
Numeric types:
Data Type | Explanation |
---|---|
bigint |
A signed 8 byte integer. |
bigserial |
An auto-incrementing 8 byte integer. |
double precision |
An 8 byte double precision floating-point number. |
integer |
A signed 4 byte integer. |
numeric or decimal |
A number of selectable precision, recommended for use in cases where exactness is crucial, such as monetary amounts. |
real |
A 4 byte single precision floating-point number. |
smallint |
A signed 2 byte integer. |
smallserial |
An auto-incrementing 2 byte integer. |
serial |
An auto-incrementing 4 byte integer. |
Character types:
Data Type | Explanation |
---|---|
character |
A character string with a specified fixed length. |
character varying or varchar |
A character string with a variable but limited length. |
text |
A character string of a variable, unlimited length. |
Date and time types:
Data Type | Explanation |
---|---|
date |
A calendar date consisting of the day, month, and year. |
interval |
A time span. |
time or time without time zone |
A time of day, not including the time zone. |
time with time zone |
A time of day, including the time zone. |
timestamp or timestamp without time zone |
A date and time, not including the time zone. |
timestamp with time zone |
A date and time, including the time zone. |
Geometric types:
Data Type | Explanation |
---|---|
box |
A rectangular box on a plane. |
circle |
A circle on a plane. |
line |
An infinite line on a plane. |
lseg |
A line segment on a plane. |
path |
A geometric path on a plane. |
point |
A geometric point on a plane. |
polygon |
A closed geometric path on a plane. |
Network address types:
Data Type | Explanation |
---|---|
cidr |
An IPv4 or IPv6 network address. |
inet |
An IPv4 or IPv6 host address. |
macaddr |
A Media Access Control (MAC) address. |
Bit string types:
Data Type | Explanation |
---|---|
bit |
A fixed-length bit string. |
bit varying |
A variable-length bit string. |
Text search types:
Data Type | Explanation |
---|---|
tsquery |
A text search query. |
tsvector |
A text search document. |
JSON types:
Data Type | Explanation |
---|---|
json |
Textual JSON data. |
jsonb |
Decomposed binary JSON data. |
Other data types:
Data Type | Explanation |
---|---|
boolean |
A logical Boolean, representing either true or false . |
bytea |
Short for “byte array”, this type is used for binary data. |
money |
An amount of currency. |
pg_lsn |
A PostgreSQL Log Sequence Number. |
txid_snapshot |
A user-level transaction ID snapshot. |
uuid |
A universally unique identifier. |
xml |
XML data. |
Today, SQLite, MySQL, and PostgreSQL are the three most popular open-source relational database management systems in the world. Each has its own unique features and limitations, and excels in particular scenarios. There are quite a few variables at play when deciding on an RDBMS, and the choice is rarely as simple as picking the fastest one or the one with the most features. The next time you’re in need of a relational database solution, be sure to research these and other tools in depth to find the one that best suits your needs.
If you’d like to learn more about SQL and how to use it to manage a relational database, we encourage you to refer to our How To Manage an SQL Database cheat sheet. On the other hand, if you’d like to learn about non-relational (or NoSQL) databases, check out our Comparison Of NoSQL Database Management Systems.
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There’s a whole lot of things missing from the PostgreSQL benefits section. Just off the top of my head:
Full Text Search
PG has full text search capabilities that rival standalone dedicated search engines like Solr, Sphinx, and Elastic Search. The full text search that exists in MySQL is scary by comparison. If your are only searching data in the database, its the way do go. You don’t have to setup and manage another system. You don’t have to worry about data syncing issues either or encoding issues transitioning your data from PG to another search engine. It has multiple dictionaries that you can implement all over the place. You can even add your own, weight searchable parts, etc.
Multi Index Queries
This is big and ties into the previous one. By default, PostgreSQL does multi-index queries so when you’re creating an index you just add them for individual columns that you will need to search on. You don’t need to create an index over multiple fields unless it’s there to maintain uniqueness across multiple fields.
Combined with the built in full text search, that means that you can just add the full text search to any where clause and all of the indexes for other items will be hit as well.
Custom data types
PG is extensible and allows the creation of custom data types as well as having 2 types of indexes built for working with those custom data types. JSON and hstore were mentioned earlier and they are the result of this. There are many other custom data types (XML, ISBN, etc) to handle just about any need that you could have…and since PG handles multi-index queries…well, that’s awesome.
Functions are amazing
Database functions are great for use in queries or manipulating data that comes back, but PostgreSQL takes them to another level. You can you create an index with the results of a function that will automatically get used when the matching function is used in a where clause. Things like a unique index on a lowercase username come to mind. This is extremely helpful if you’re working with XML too because you can’t index an XML file…but you can index the result of an XPATH function on the XML datatype.
Wasted space is TOASTed
TOAST is the compression layer behind PG’s TEXT field types. It automatically zip’s large data. I dropped a 2.2 mb XML file in and it stored in as 81 kb.
Stored procedures aren’t painful
You can write stored procedures in other languages including Python and Javascript. This makes putting logic that belongs in your database in there a whole lot simpler.
LISTEN/NOTIFY will change your life
Never have a long running process poll for changes to data again. Long running server processes can now hold a connection and let the database tell them when a change happened. These remove your dependence on framework “AFTER SAVE” hooks, which really comes in handy when you need to connect to your database with another language. If it changes in the database, it changes everywhere.
A few quick use cases for this:
PostGIS for Geospatial Data
Adds a bunch of custom datatypes and logic for dealing with geospatial data. Because you can do that with PostgreSQL.
Because of multi-index queries, this means that in one query you can search for basic where conditions, full text, and filter by geospatial parameters like distance. In ONE. DANG. QUERY.
This is off the top of my head. There’s a lot more.
The date-time type of MySQL doesn’t store the time zone. In PostrgeSQL, it does.
Please rename “Glossary” to “Table of Contents”
One year and half for this article, can you update it please ?
As other’s have said JSON support in PostgreSQL is a huge benefit over other RDBMS. The fact that I can throw in a simple JSON object and then query against its property fields using a SQL query makes PostgreSQL immensely powerful.
“Unless you require absolute data integrity, ACID compliance or complex designs, PostgreSQL can be an over-kill for simple set-ups.”
People who don’t need those things probably have no business using a database at all. It’s shocking how many people think that the average self-hosted Wordpress site is actually dynamic and thus requires a database. The vast majority of things out there using a database are static sites with a silly, over-engineered backend.
Postgres JSON data type is a huge advantage over MySQL.
I would like to point out that the JSON and hstore datatypes in PostgreSQL aren’t mentioned, and are extremely useful.
I question the claim that MySQL is “The most popular and commonly used RDBMS”. It depends on what you mean by “popular and commonly used”, but SQLite is used almost everywhere these days. I honestly don’t know how to do anything on my computer or phone today that doesn’t use SQLite. It’s in iOS and Android, it’s in Firefox and Chrome, it’s in OS X (and used by every OS X application, indirectly, and several of them directly) and Linux. It’s used by Dropbox and Skype and Lightroom and Airbus and pretty much every major software company in the world.
MySQL is very popular for web apps, but SQLite is very popular for basically everything else.
Just joined D.O. because of this post. Great information for someone looking to get more familiar with databases. Thanks to everyone who commented as well.