DBMS > AgensGraph vs. Cassandra vs. Couchbase vs. Newts vs. RDF4J

System Properties Comparison AgensGraph vs. Cassandra vs. Couchbase vs. Newts vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Time Series DBMS based on Cassandra

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

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

bitnine.net/agensgraph

cassandra.apache.org

www.couchbase.com

opennms.github.io/newts

rdf4j.org

Technical documentation

bitnine.net/documentation

cassandra.apache.org/doc/latest

docs.couchbase.com

github.com/OpenNMS/newts/wiki

rdf4j.org/documentation

Developer

Bitnine Global Inc.

Apache Software Foundation

Apache top level project, originally developped by Facebook

Couchbase, Inc.

OpenNMS Group

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

Initial release

2016

2008

2011

2014

2004

Current release

2.1, December 2018

4.1.3, July 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache version 2

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

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

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

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C, C++, Go and Erlang

Java

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

depending on used data model

schema-free

yes

RDF Schemas

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

SQL-like SELECT, DML and DDL statements (CQL)

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

Cypher Query Language
JDBC

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

HTTP REST
Java API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
Java
JavaScript
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

no "single point of failure"

Automatic Sharding

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Ephemeral buckets

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

More information provided by the system vendor

Specific characteristics

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Market metrics

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Licensing and pricing models

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