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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. IBM DB2 vs Oracle

IBM DB2 vs Oracle

OverviewDecisionsComparisonAlternatives

Overview

Oracle
Oracle
Stacks2.6K
Followers1.8K
Votes113
IBM DB2
IBM DB2
Stacks245
Followers254
Votes19

IBM DB2 vs Oracle: What are the differences?

Introduction

In the world of relational database management systems, IBM DB2 and Oracle are two prominent players. Although they both offer powerful capabilities, there are key differences that set them apart. In this article, we will explore six important distinctions between IBM DB2 and Oracle.

  1. Cost Model: One significant difference between IBM DB2 and Oracle is their cost model. IBM DB2 follows a user-based licensing model, where the cost is determined by the number of users accessing the database. On the other hand, Oracle uses a processor-based licensing model, where the cost depends on the number of processors or cores used for running the database. This difference in cost models can greatly impact the financial considerations when choosing between the two.

  2. Platform Support: When it comes to platform support, IBM DB2 and Oracle have differing levels of compatibility. IBM DB2 offers broader platform support, with versions available for various operating systems including Windows, Linux, Unix, and z/OS. In contrast, Oracle has a more limited range of supported platforms, primarily focusing on Windows and Oracle Linux. Therefore, if you require a specific platform compatibility, this difference becomes a crucial factor.

  3. Data Types: Another area where IBM DB2 and Oracle differ is in their data type offerings. IBM DB2 provides a wider range of built-in data types, including robust support for XML and LOB (Large Object) data types. Oracle, on the other hand, offers fewer built-in data types but provides more extensive support for spatial data types and advanced features like JSON data handling. The choice of database depends on the specific data type requirements of the application.

  4. SQL Syntax: IBM DB2 and Oracle also exhibit syntax differences in their SQL implementation. While both databases comply with SQL standards to a great extent, they have minor variations in syntax and proprietary extensions. Developers accustomed to one database may face a learning curve when switching to the other. Therefore, SQL syntax compatibility is an essential consideration for organizations with existing applications or skilled developers.

  5. Scalability and Performance: Scalability and performance are crucial factors for any database system. Both IBM DB2 and Oracle are known for their scalability, but they utilize different approaches. Oracle utilizes a shared-everything architecture, where all the physical resources are shared across multiple instances. IBM DB2, on the other hand, adopts a shared-nothing architecture with database partitioning, allowing each partition to run independently. Depending on the workload and requirements, the choice between these architectures can significantly impact the performance and scalability of the database system.

  6. Feature Set: Finally, the feature set offered by IBM DB2 and Oracle has notable differences. While both databases provide essential features like high availability, security, and transaction management, they have unique features that set them apart. IBM DB2 offers notable features such as deep compression, BLU acceleration technology for analytics, and integration with IBM's Watson AI platform. Oracle, on the other hand, is known for its advanced features like Real Application Clusters (RAC), Oracle Exadata for optimized performance, and advanced data replication capabilities. The choice between IBM DB2 and Oracle depends on the specific features required for the application and business needs.

In summary, IBM DB2 and Oracle differ in their cost models, platform support, data types, SQL syntax, scalability and performance approaches, and feature sets. Understanding these key differences is crucial in making an informed decision while selecting the most suitable database management system for your organization.

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Advice on Oracle, IBM DB2

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.

495k views495k
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 DB2
IBM DB2

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.

DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs.

Statistics
Stacks
2.6K
Stacks
245
Followers
1.8K
Followers
254
Votes
113
Votes
19
Pros & Cons
Pros
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Expensive
  • 5
    Hard to maintain
Cons
  • 14
    Expensive
Pros
  • 7
    Rock solid and very scalable
  • 5
    BLU Analytics is amazingly fast
  • 2
    Easy
  • 2
    Secure by default
  • 2
    Native XML support
Integrations
No integrations available
Node.js
Node.js
JavaScript
JavaScript
PHP
PHP
Ruby
Ruby
Java
Java
Python
Python
C#
C#
.NET
.NET
C++
C++
Perl
Perl

What are some alternatives to Oracle, IBM DB2?

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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