DBMS > AnzoGraph DB vs. H2 vs. HyperSQL vs. Oracle vs. TDSQL for MySQL

System Properties Comparison AnzoGraph DB vs. H2 vs. HyperSQL vs. Oracle vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used RDBMS

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS

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

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.h2database.com

hsqldb.org

www.oracle.com/database

www.tencentcloud.com/products/dcdb

Technical documentation

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

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

docs.oracle.com/en/database

www.tencentcloud.com/document/product/1042

Developer

Cambridge Semantics

Thomas Mueller

Oracle

Tencent

Initial release

2018

2005

2001

1980

2013

Current release

2.3, January 2021

2.2.220, July 2023

2.7.2, June 2023

23c, September 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

based on BSD license

commercial

restricted free version is available

commercial

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

C and C++

Server operating systems

Linux

All OS with a Java VM

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

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

with proprietary extensions

yes

APIs and other access methods

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

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

Supported programming languages

C++
Java
Python

Java

All languages supporting JDBC/ODBC
Java

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures and User-Defined Functions

Java, SQL

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding, horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

With clustering: 2 database servers on different computers operate on identical copies of a database

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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