DBMS > AnzoGraph DB vs. H2 vs. MySQL vs. XTDB

System Properties Comparison AnzoGraph DB vs. H2 vs. MySQL vs. XTDB

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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.

Widely used open source RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Spatial DBMS

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	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

cambridgesemantics.com/anzograph

www.h2database.com

www.mysql.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.h2database.com/html/main.html

dev.mysql.com/doc

www.xtdb.com/docs

Developer

Cambridge Semantics

Thomas Mueller

Oracle

since 2010, originally MySQL AB, then Sun

Juxt Ltd.

Initial release

2018

2005

1995

2019

Current release

2.3, January 2021

2.2.220, July 2023

8.4.0, April 2024

1.19, September 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

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

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

Clojure

Server operating systems

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST
JDBC

Supported programming languages

C++
Java
Python

Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

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

Multi-source replication
Source-replica replication

yes, each node contains all data

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 in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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