DBMS > Informix vs. Oracle Berkeley DB vs. Oracle NoSQL vs. Sadas Engine

System Properties Comparison Informix vs. Oracle Berkeley DB vs. Oracle NoSQL vs. Sadas Engine

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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

Widely used in-process key-value store

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

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

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

www.ibm.com/products/informix

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

www.oracle.com/database/nosql/technologies/nosql

www.sadasengine.com

Technical documentation

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

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

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.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle

SADAS s.r.l.

Initial release

1984

1994

2011

2006

Current release

14.10.FC5, November 2020

18.1.40, May 2020

24.1, May 2024

8.0

License

Commercial or Open Source

commercial

free developer edition available

Open Source

commercial license available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and Java

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

Java

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
Solaris SPARC/x86

AIX
Linux
Windows

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

optional

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

SQL interfaced based on SQLite is available

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
JSON API

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

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

.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

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

managed by 'Learn by Usage'

User concepts

Access control

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

Access rights for users and roles

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

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