Technical Comparison between Oracle, MySQL and PostgreSQL

A database is a collection of information that is structured in such a way that it is easy to manage and update. To make this task easier various Database Management Systems(DBMS) have been created. These include MySQL, PostgreSQL, Oracle etc.

Mysql is one of the most famous, open-source Relational database management system (RDMS). The data in this table is stored in tables which makes it easy to perform CRUD operations (Create, Read, Update and Delete). Mysql is fast, easy and reliable. It can be used for both large and small applications and it provide high scalability. But it doesn’t provide support for materialised views and table inheritance and only support Standard data types.

PostgreSQL is a powerful, open-source Object-relational database system. It provides good performance with low maintenance efforts because of its high stability. PostgreSQL was the first DBMS that implemented multi-version concurrency control (MVCC) feature. It support for vast amount of languages. It provides advanced security features and it has geo – tagging support.

Oracle is a relational database management system created and run by the Oracle Corporation. Currently, it supports multiple data models like document, graph, relational, and key-value within the single database. In its latest releases, it refocused on cloud computing. Oracle database engine licensing is fully proprietary, with both free and paid options available. It have More functional than PostgreSQL, but these functions come at a price premium. It have more robust security features than PostgreSQL

	MySQL	PostgreSQL	Oracle
Server Operating System	FreeBSD, Linux, OS X, Solaris, and Windows	FreeBSD, HP-UX, Linux, NetBSD, OpenBSD, OS X, Solaris, Unix and Windows	AIX, HP-UX, Linux, OS X, Solaris, Windows, z/OS
Supported Programming Languages	Ada, C, C#, C++, D, Delphi, Eiffel, Erlang, Haskell, Java, JavaScript, Objective-C, OCaml, Perl, PHP, Python, Ruby, Scheme, and Tcl	It supports.Net, C, C++, Delphi, Java, JavaScript, Perl, PHP, Python, and Tcl	C, C#, C++, Clojure, Cobol, Delphi, Eiffel, Erlang, Fortran, Groovy, Haskell, Java, JavaScript, Lisp, Objective C, OCaml, Perl, PHP, Python, R, Ruby, Scala, Tcl, Visual Basic
Implementation language	C and C++	C	C and C++
Licensing	Open Source	Open Source	Commercial
Drop Tables	Possible	Possible	Possible
Functional Indexes	Absent	Present	Present in 8i
Partial Indexes	Absent	Present	Present
UPSERT Logic	Absent	Absent	Present
Dynamic and Action SQL in functions	Absent( But, it can be done in stored procedures)	Present	Present
Support Creation of Functions	It also has standard Db security with table-driven security	It has extensive security with standard, LDAP, SSPI, PAM, trust etc	Standard Db security
Case-insensitivity	Case-insensitive	Case-sensitive	Case-insensitive
In-memory capabilities	Yes	No	Yes

Conclusion

Many database administrators think that the performance of MySQL is better than PostgreSQL. On the other hand, Oracle has more reliable recovery methods than MySQL. Oracle too supports various programming languages and it has robust recovery methods. The most significant thing is MySQL supports both UNIX and Linux. Oracle too supports Unix and Linux. The thing to remember is that all these three databases are active and robust and are widely used in the market. This post will explain the technical difference between these three databases.

MySQL is one of the most popular relational database systems. Originally an open-source solution, MySQL now is owned by Oracle Corporation.

When you look at PostgreSQL vs. Oracle database management systems, the main difference is that PostgreSQL is an open-source database, while Oracle is a closed database system. PostgreSQL is a free relational object-oriented database management system that is developed by volunteer developers worldwide. Oracle is a licensed commercial relational database management system.

Both database systems use similar concepts such as schemas, tables paces and indices, but they diverge in areas such as replication and support. Let’s explore the ways that these two database systems handle vital operations.