DBMS > Badger vs. Bangdb vs. Geode vs. RDF4J

System Properties Comparison Badger vs. Bangdb vs. Geode vs. RDF4J

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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.

Converged and high performance database for device data, events, time series, document and graph

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Key-value store

Document store
Graph DBMS
Time Series DBMS

Key-value store

RDF store

Secondary database models

Spatial DBMS

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

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

github.com/dgraph-io/badger

bangdb.com

geode.apache.org

rdf4j.org

Technical documentation

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

docs.bangdb.com

geode.apache.org/docs

rdf4j.org/documentation

Developer

DGraph Labs

Sachin Sinha, BangDB

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2017

2012

2002

2004

Current release

BangDB 2.0, October 2021

1.1, February 2017

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD 3

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Eclipse Distribution License (EDL), v1.0.

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++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language (OQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
C++
Java
Python

.Net
All JVM based languages
C++
Groovy
Java
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes, Notifications (with Streaming only)

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable consistency, set CAP knob accordingly

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes, on a single node

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

in-memory storage is supported as well

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights per client and object definable

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