DBMS > Amazon Neptune vs. AnzoGraph DB vs. GraphDB

System Properties Comparison Amazon Neptune vs. AnzoGraph DB vs. GraphDB

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Graph DBMS
RDF store

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.21
Rank	#308	Overall
	#25	Graph DBMS
	#15	RDF stores

Score	2.59
Rank	#96	Overall
	#7	Graph DBMS
	#3	RDF stores

Website

aws.amazon.com/neptune

cambridgesemantics.com/anzograph

www.ontotext.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

graphdb.ontotext.com/documentation

Developer

Amazon

Cambridge Semantics

Ontotext

Initial release

2017

2018

2000

Current release

2.3, January 2021

10.4, October 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

Some plugins of GraphDB Workbench are open sourced

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

Server operating systems

hosted

Linux

All OS with a Java VM
Linux
OS X
Windows

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

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

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

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

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

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

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

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C++
Java
Python

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

Server-side scripts

Stored procedures

user defined functions and aggregates

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication in MPP-Cluster

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

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

Foreign keys

Referential integrity

yes

Relationships in graphs

not needed 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

Durability

Support for making data persistent

yes

with encyption-at-rest

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles

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.

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More resources

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