DBMS > AgensGraph vs. AnzoGraph DB vs. HyperSQL

System Properties Comparison AgensGraph vs. AnzoGraph DB vs. HyperSQL

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Editorial information provided by DB-Engines

Name

Description

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

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Graph DBMS
Relational DBMS

Graph DBMS
RDF store

Relational 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	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

bitnine.net/agensgraph

cambridgesemantics.com/anzograph

hsqldb.org

Technical documentation

bitnine.net/documentation

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

hsqldb.org/web/hsqlDocsFrame.html

Developer

Bitnine Global Inc.

Cambridge Semantics

Initial release

2016

2018

2001

Current release

2.1, December 2018

2.3, January 2021

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free trial version available

Open Source

based on BSD license

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

Server operating systems

Linux
OS X
Windows

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

depending on used data model

Schema-free and OWL/RDFS-schema support

yes

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

SQL

Support of SQL

yes

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

yes

APIs and other access methods

Cypher Query Language
JDBC

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

C++
Java
Python

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication in MPP-Cluster

none

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

Foreign keys

Referential integrity

yes

not needed in graphs

yes

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

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

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