DBMS > ArcadeDB vs. Bangdb vs. Galaxybase vs. GraphDB

System Properties Comparison ArcadeDB vs. Bangdb vs. Galaxybase vs. GraphDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

Scalable, ACID-compliant native distributed parallel graph platform

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store
Graph DBMS
Time Series DBMS

Graph DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Website

Technical documentation

docs.arcadedb.com

docs.bangdb.com

graphdb.ontotext.com/documentation

Social network pages

Developer

Arcade Data

Sachin Sinha, BangDB

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Ontotext

Initial release

2021

2012

2017

2000

Current release

September 2021

BangDB 2.0, October 2021

Nov 20, November 2021

10.4, October 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD 3

commercial

Some plugins of GraphDB Workbench are open sourced

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

Java

C, C++

C and Java

Java

Server operating systems

All OS with a Java VM

Linux

All OS with a Java VM
Linux
OS X
Windows

Data scheme

schema-free

Strong typed schema

schema-free and OWL/RDFS-schema support; RDF shapes

Typing

predefined data types such as float or date

yes

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

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

SQL

Support of SQL

SQL-like query language, no joins

SQL like support with command line tool

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

Proprietary protocol
RESTful HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

Supported programming languages

Java

C
C#
C++
Java
Python

Go
Java
Python

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined procedures and functions

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

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

Source-replica replication

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

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Relationships in graphs

yes

Constraint checking

Transaction concepts

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

ACID

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 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)

Role-based access control

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Migrating From LPG to RDF Graph Model
8 May 2024

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

Scaling Understanding with the Help of Feedback Loops, Knowledge Graphs and NLP
19 April 2024

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

做国产图数据库，「创邻科技」将拓展国际市场| 新科技创业
5 April 2023, 36kr

创邻科技，位居IDC MarketScape中国图数据库市场领导者类别
13 September 2023, CSDN

provided by Google News

Ontotext's GraphDB Solution is Now Available on the Microsoft Azure Marketplace
16 January 2024, PR Newswire

Ontotext Unveils GraphDB 10.4 with Enhanced AWS Integration and ChatGPT Connector
24 October 2023, Datanami

Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released
18 December 2019, KDnuggets

It's just semantics: Bulgarian software dev Ontotext squeezes out GraphDB 9.1
15 January 2020, The Register

Ontotext's GraphDB 10 Brings Modern Data Architectures to the Mainstream with Better Resilience and Еаsier Operations
5 July 2022, PR Newswire

provided by Google News

Share this page