IBM DB2 vs Microsoft SQL Server

Overview

Microsoft SQL Server

Stacks21.3K

Followers15.5K

Votes540

IBM DB2

Stacks245

Followers254

Votes19

IBM DB2 vs Microsoft SQL Server: What are the differences?

Both DB2 and SQL Server are popular relational database management systems used by organizations to store and manage their data efficiently. Let's explore the key differences between them.

Licensing Model: The licensing models for IBM DB2 and Microsoft SQL Server differ significantly. DB2 follows a processor-based licensing model, where the cost is based on the number of processor cores on the server. On the other hand, SQL Server follows a combination of Core-based and Server+CAL (Client Access License) licensing models. Core-based licensing requires purchasing licenses for each server core, while Server+CAL licensing requires licenses for both the server and the number of users or devices accessing the server.
Supported Platforms: DB2 is known for its extensive platform support and runs on various operating systems, including Windows, Linux, Unix, and z/OS. In contrast, SQL Server primarily runs on Windows operating systems. While there is a version called SQL Server on Linux, it does not have the same level of platform support as DB2 across multiple operating systems.
Data Type Support: Both DB2 and SQL Server provide support for a wide range of data types. DB2 offers a richer set of native data types, including built-in support for large objects (CLOBs, BLOBs) and pureXML. SQL Server, on the other hand, offers an extensive set of data types but does not have native support for large objects. Instead, it uses the VarBinary data type as an alternative.
Query Optimization: DB2 and SQL Server utilize different query optimization techniques. DB2 employs a cost-based query optimizer that estimates the cost of various access paths and chooses the most efficient one for a given query. SQL Server, on the other hand, uses a rule-based query optimizer that relies on a set of predefined rules to determine the execution plan. While both optimizers aim to improve performance, the approach and optimization techniques differ between the two systems.
SQL Dialect: Although both DB2 and SQL Server are based on the SQL (Structured Query Language) standard, there are certain variances in the SQL dialect they support. DB2 follows the ISO SQL:2003 standard more closely, whereas SQL Server has its own proprietary SQL extensions and syntax. This difference in SQL dialects may require slight modifications to queries when migrating them between the two databases.
Full-Text Search: Full-text search capabilities in DB2 and SQL Server also exhibit differences. DB2 provides its own built-in full-text search engine called Text Search, which allows users to perform advanced text-based searches across multiple columns. SQL Server offers a similar feature called Full-Text Search, which enables efficient searching through large amounts of text stored in SQL Server databases. While both systems provide full-text search capabilities, the underlying mechanisms and syntax may differ.

In summary, DB2 is known for its scalability and support for various platforms, while SQL Server is recognized for its integration with Microsoft technologies and comprehensive business intelligence capabilities.

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Advice on Microsoft SQL Server, IBM DB2

Erin

IT Specialist

Mar 10, 2020

Needs adviceon

Microsoft SQL Server

MySQL

PostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.

668k views668k

Comments

Josip

Senior frontend developer

Aug 31, 2021

Decided

Needed to transform intranet desktop application to the web-based one, as mid-term project. My choice was to use Django/Angular stack - Django since it, in conjunction with Python, enabled rapid development, an Angular since it was stable and enterprise-level framework. Deadlines were somewhat tight since the project to migrate was being developed for several years and had a lot of domain knowledge integrated into it. Definitely was good decision, since deadlines was manageable, juniors were able to enter the project very quickly and we were able to continuously deploy very well.

73.6k views73.6k

Comments

Detailed Comparison

Microsoft SQL Server	IBM DB2
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.	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 21.3K	Stacks 245
Followers 15.5K	Followers 254
Votes 540	Votes 19
Pros & Cons
Pros 139 Reliable and easy to use 101 High performance 95 Great with .net 65 Works well with .net 56 Easy to maintain Cons 4 Expensive Licensing 2 Microsoft 1 The maximum number of connections is only 14000 connect 1 Replication can loose the data 1 Allwayon can loose data in asycronious mode	Pros 7 Rock solid and very scalable 5 BLU Analytics is amazingly fast 2 Secure by default 2 Native XML support 2 Easy
Integrations
No integrations available	Node.js JavaScript PHP Ruby Java Python C# .NET C++ Perl

What are some alternatives to Microsoft SQL Server, IBM DB2?

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

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 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.

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

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 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

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 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

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.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

IBM DB2 vs Microsoft SQL Server: What are the differences?

Both DB2 and SQL Server are popular relational database management systems used by organizations to store and manage their data efficiently. Let's explore the key differences between them.

Licensing Model: The licensing models for IBM DB2 and Microsoft SQL Server differ significantly. DB2 follows a processor-based licensing model, where the cost is based on the number of processor cores on the server. On the other hand, SQL Server follows a combination of Core-based and Server+CAL (Client Access License) licensing models. Core-based licensing requires purchasing licenses for each server core, while Server+CAL licensing requires licenses for both the server and the number of users or devices accessing the server.
Supported Platforms: DB2 is known for its extensive platform support and runs on various operating systems, including Windows, Linux, Unix, and z/OS. In contrast, SQL Server primarily runs on Windows operating systems. While there is a version called SQL Server on Linux, it does not have the same level of platform support as DB2 across multiple operating systems.
Data Type Support: Both DB2 and SQL Server provide support for a wide range of data types. DB2 offers a richer set of native data types, including built-in support for large objects (CLOBs, BLOBs) and pureXML. SQL Server, on the other hand, offers an extensive set of data types but does not have native support for large objects. Instead, it uses the VarBinary data type as an alternative.
Query Optimization: DB2 and SQL Server utilize different query optimization techniques. DB2 employs a cost-based query optimizer that estimates the cost of various access paths and chooses the most efficient one for a given query. SQL Server, on the other hand, uses a rule-based query optimizer that relies on a set of predefined rules to determine the execution plan. While both optimizers aim to improve performance, the approach and optimization techniques differ between the two systems.
SQL Dialect: Although both DB2 and SQL Server are based on the SQL (Structured Query Language) standard, there are certain variances in the SQL dialect they support. DB2 follows the ISO SQL:2003 standard more closely, whereas SQL Server has its own proprietary SQL extensions and syntax. This difference in SQL dialects may require slight modifications to queries when migrating them between the two databases.
Full-Text Search: Full-text search capabilities in DB2 and SQL Server also exhibit differences. DB2 provides its own built-in full-text search engine called Text Search, which allows users to perform advanced text-based searches across multiple columns. SQL Server offers a similar feature called Full-Text Search, which enables efficient searching through large amounts of text stored in SQL Server databases. While both systems provide full-text search capabilities, the underlying mechanisms and syntax may differ.

IBM DB2 vs Microsoft SQL Server

Overview