DBMS > Informix vs. Microsoft SQL Server vs. openGauss vs. Oracle Berkeley DB

System Properties Comparison Informix vs. Microsoft SQL Server vs. openGauss vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

Microsofts flagship relational DBMS

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Widely used in-process key-value store

Primary database model

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

www.ibm.com/products/informix

www.microsoft.com/en-us/sql-server

gitee.com/opengauss
opengauss.org

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

learn.microsoft.com/en-US/sql/sql-server

docs.opengauss.org/en
gitee.com/opengauss/docs

docs.oracle.com/cd/E17076_05/html/index.html

Developer

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Microsoft

Huawei and openGauss community

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

1984

1989

2019

1994

Current release

14.10.FC5, November 2020

SQL Server 2022, November 2022

3.0, March 2022

18.1.40, May 2020

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

Open Source

commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and Java

C++

C, C++, Java

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
Windows

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL 2011

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Java

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning (by range, list and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users with fine-grained authentication, authorization, and auditing controls

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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