DBMS > Badger vs. IBM Db2 vs. Oracle NoSQL

System Properties Comparison Badger vs. IBM Db2 vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

Primary database model

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

github.com/dgraph-io/badger

www.ibm.com/products/db2

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

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.ibm.com/docs/en/db2

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

Developer

DGraph Labs

IBM

Oracle

Initial release

2017

1983

host version

2011

Current release

12.1, October 2016

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free version is available

Open Source

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

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 and C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Solaris SPARC/x86

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

optional

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

RESTful HTTP API

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

only with Windows/Unix/Linux Version

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

with separate tools (MQ, InfoSphere)

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

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

depending on configuration

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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