DBMS > BigObject vs. GraphDB vs. IBM Cloudant vs. KairosDB

System Properties Comparison BigObject vs. GraphDB vs. IBM Cloudant vs. KairosDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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.

Database as a Service offering based on Apache CouchDB

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Graph DBMS
RDF store

Document store

Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Website

bigobject.io

www.ontotext.com

www.ibm.com/products/cloudant

github.com/kairosdb/kairosdb

Technical documentation

docs.bigobject.io

graphdb.ontotext.com/documentation

cloud.ibm.com/docs/Cloudant

kairosdb.github.io

Social network pages

Developer

BigObject, Inc.

Ontotext

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2015

2000

2010

2013

Current release

10.4, October 2023

1.2.2, November 2018

License

Commercial or Open Source

commercial

free community edition available

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

Open Source

Apache 2.0

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

Java

Erlang

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM
Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

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

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.

Secondary indexes

yes

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

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

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

RESTful HTTP/JSON API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

well-defined plugin interfaces; JavaScript server-side extensibility

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Constraint checking

Transaction concepts

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

ACID

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Optimistic locking

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

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.

Access rights for users can be defined per database

simple password-based access control

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

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29 May 2024

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17 May 2024

Migrating From LPG to RDF Graph Model
8 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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