DBMS > Badger vs. DataFS vs. EsgynDB vs. IBM Db2 warehouse

System Properties Comparison Badger vs. DataFS vs. EsgynDB vs. IBM Db2 warehouse

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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.

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Cloud-based data warehousing service

Primary database model

Key-value store

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Website

github.com/dgraph-io/badger

newdatabase.com

www.esgyn.cn

www.ibm.com/products/db2/warehouse

Technical documentation

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

dev.mobiland.com/Overview.xsp

Developer

DGraph Labs

Mobiland AG

Esgyn

IBM

Initial release

2017

2018

2015

2014

Current release

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Windows

Linux

hosted

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

PL/SQL, SQL PL

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Windows-Profile

fine grained access rights according to SQL-standard

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