DBMS > Amazon Redshift vs. AnzoGraph DB vs. EsgynDB vs. RDF4J vs. SurrealDB

System Properties Comparison Amazon Redshift vs. AnzoGraph DB vs. EsgynDB vs. RDF4J vs. SurrealDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Document store
Graph DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

aws.amazon.com/redshift

cambridgesemantics.com/anzograph

www.esgyn.cn

rdf4j.org

surrealdb.com

Technical documentation

docs.aws.amazon.com/redshift

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

rdf4j.org/documentation

surrealdb.com/docs

Developer

Amazon (based on PostgreSQL)

Cambridge Semantics

Esgyn

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

SurrealDB Ltd

Initial release

2012

2018

2015

2004

2022

Current release

2.3, January 2021

v1.5.0, May 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

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

C++, Java

Java

Rust

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

RDF Schemas

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Java
PHP
Python

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

not needed in graphs

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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