DBMS > Badger vs. MaxDB vs. Oracle Berkeley DB

System Properties Comparison Badger vs. MaxDB vs. Oracle Berkeley DB

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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.

A robust and reliable RDBMS optimized to run all major SAP solutions

Widely used in-process key-value store

Primary database model

Key-value store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.13
Rank	#371	Overall
	#57	Key-value stores

Score	3.37
Rank	#102	Overall
	#49	Relational DBMS

Score	3.38
Rank	#101	Overall
	#19	Key-value stores
	#3	Native XML DBMS

Website

github.com/dgraph-io/badger

maxdb.sap.com

www.oracle.com/technetwork/database/database-technologies/berkeleydb/overview/index.html

Technical documentation

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

maxdb.sap.com/documentation

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

Developer

DGraph Labs

SAP, acquired from Software AG (Adabas-D) in 1997

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2017

1984

1994

Current release

7.9.10 (January 2020), 2020

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited community edition free

Open Source

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

APIs and other access methods

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

.Net
C#
Java
Perl
PHP
Python

.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

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

fine grained access rights according to SQL-standard

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