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  1. Stackups
  2. Application & Data
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  4. Databases
  5. IBM Informix vs Oracle

IBM Informix vs Oracle

OverviewDecisionsComparisonAlternatives

Overview

Oracle
Oracle
Stacks2.6K
Followers1.8K
Votes113
IBM Informix
IBM Informix
Stacks17
Followers26
Votes0

IBM Informix vs Oracle: What are the differences?

Key Differences between IBM Informix and Oracle

Introduction:

IBM Informix and Oracle are two popular database management systems (DBMS) used by organizations for storing and managing their data. While they have similarities in terms of being relational databases, there are several key differences that set them apart.

  1. Scalability: IBM Informix is known for its exceptional scalability, allowing users to efficiently handle large volumes of data and support high transaction rates. It is optimized for online transaction processing (OLTP) workloads and offers features like distributed data and high availability clustering. On the other hand, Oracle also provides scalability options but tends to be more resource-intensive, making it suitable for workloads that demand high performance and complex processing.

  2. Cost: Cost is another major differentiating factor between IBM Informix and Oracle. Generally, Informix is considered to be more cost-effective in terms of licensing and maintenance, making it a preferred choice for organizations with budget constraints. In contrast, Oracle is known for its enterprise-grade features and comprehensive toolset, which often come at a higher price point.

  3. Ease of Use and Administration: IBM Informix is designed to be user-friendly and offers a straightforward administration process. It provides a simplified interface and intuitive query language, which accelerates development and reduces the learning curve for developers and administrators. Oracle, on the other hand, offers a rich set of tools and functionalities, which can result in a steeper learning curve and require more expertise for administration tasks.

  4. Performance: Both IBM Informix and Oracle are capable of delivering high performance, but they excel in different areas. Informix is well-regarded for its superior performance in OLTP workloads, where it leverages its optimized architecture and efficient transaction processing capabilities. Oracle, on the other hand, shines in complex analytical tasks and data warehousing, making it a preferred choice for organizations that require extensive data analysis and reporting capabilities.

  5. Replication and High Availability Features: IBM Informix offers robust replication and high availability features, including support for high-speed data transfer and synchronization across multiple database instances. This makes it suitable for businesses that need real-time data updates and require seamless failover capabilities. Oracle also provides replication and high availability features but often requires additional configurations and specialized tools to achieve similar functionality.

  6. Ecosystem and Third-Party Support: Oracle has a vast ecosystem and enjoys strong third-party support, making it easier for organizations to find resources, tools, and professional services related to the Oracle DBMS. It is well-integrated with various software applications, development frameworks, and reporting tools, providing a comprehensive ecosystem for developers. While Informix enjoys a loyal user base, it may have comparatively fewer third-party integrations and may require additional effort for integration with specific applications.

In Summary, IBM Informix excels in scalability, cost-effectiveness, ease of use, and performance in OLTP workloads, while Oracle is renowned for its comprehensive toolset, performance in analytical tasks, and strong ecosystem support.

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Advice on Oracle, IBM Informix

Daniel
Daniel

Data Engineer at Dimensigon

Jul 18, 2020

Decided

We have chosen Tibero over Oracle because we want to offer a PL/SQL-as-a-Service that the users can deploy in any Cloud without concerns from our website at some standard cost. With Oracle Database, developers would have to worry about what they implement and the related costs of each feature but the licensing model from Tibero is just 1 price and we have all features included, so we don't have to worry and developers using our SQLaaS neither. PostgreSQL would be open source. We have chosen Tibero over Oracle because we want to offer a PL/SQL that you can deploy in any Cloud without concerns. PostgreSQL would be the open source option but we need to offer an SQLaaS with encryption and more enterprise features in the background and best value option we have found, it was Tibero Database for PL/SQL-based applications.

496k views496k
Comments
Abigail
Abigail

Dec 6, 2019

Decided

In the field of bioinformatics, we regularly work with hierarchical and unstructured document data. Unstructured text data from PDFs, image data from radiographs, phylogenetic trees and cladograms, network graphs, streaming ECG data... none of it fits into a traditional SQL database particularly well. As such, we prefer to use document oriented databases.

MongoDB is probably the oldest component in our stack besides Javascript, having been in it for over 5 years. At the time, we were looking for a technology that could simply cache our data visualization state (stored in JSON) in a database as-is without any destructive normalization. MongoDB was the perfect tool; and has been exceeding expectations ever since.

Trivia fact: some of the earliest electronic medical records (EMRs) used a document oriented database called MUMPS as early as the 1960s, prior to the invention of SQL. MUMPS is still in use today in systems like Epic and VistA, and stores upwards of 40% of all medical records at hospitals. So, we saw MongoDB as something as a 21st century version of the MUMPS database.

540k views540k
Comments
Abigail
Abigail

Dec 10, 2019

Decided

We wanted a JSON datastore that could save the state of our bioinformatics visualizations without destructive normalization. As a leading NoSQL data storage technology, MongoDB has been a perfect fit for our needs. Plus it's open source, and has an enterprise SLA scale-out path, with support of hosted solutions like Atlas. Mongo has been an absolute champ. So much so that SQL and Oracle have begun shipping JSON column types as a new feature for their databases. And when Fast Healthcare Interoperability Resources (FHIR) announced support for JSON, we basically had our FHIR datalake technology.

558k views558k
Comments

Detailed Comparison

Oracle
Oracle
IBM Informix
IBM Informix

Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.

It is a fast and flexible database with the ability to seamlessly integrate SQL, NoSQL/JSON, and time series and spatial data. Its versatility and ease of use make Informix a preferred solution for a wide range of environments, from enterprise data warehouses to individual application development.

-
Real-time analytics; Fast, always-on transactions; Fewer data management hassles; Simple and non-disruptive
Statistics
Stacks
2.6K
Stacks
17
Followers
1.8K
Followers
26
Votes
113
Votes
0
Pros & Cons
Pros
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Hard to maintain
  • 5
    Expensive
Cons
  • 14
    Expensive
No community feedback yet
Integrations
No integrations available
Linux
Linux
macOS
macOS
Windows
Windows

What are some alternatives to Oracle, IBM Informix?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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