DBMS > AnzoGraph DB vs. Axibase vs. HyperSQL vs. MySQL vs. Netezza

System Properties Comparison AnzoGraph DB vs. Axibase vs. HyperSQL vs. MySQL vs. Netezza

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

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used open source RDBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

cambridgesemantics.com/anzograph

axibase.com/docs/atsd/finance

hsqldb.org

www.mysql.com

www.ibm.com/products/netezza

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

dev.mysql.com/doc

Developer

Cambridge Semantics

Axibase Corporation

Oracle

since 2010, originally MySQL AB, then Sun

IBM

Initial release

2018

2013

2001

1995

2000

Current release

2.3, January 2021

15585

2.7.2, June 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

based on BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

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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

FreeBSD
Linux
OS X
Solaris
Windows

Linux

included in appliance

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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.

SQL-like query language

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
Proprietary protocol (Network API)
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
OLE DB

Supported programming languages

C++
Java
Python

Go
Java
PHP
Python
R
Ruby

All languages supporting JDBC/ODBC
Java

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Java, SQL

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

none

Multi-source replication
Source-replica replication

Source-replica replication

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 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

table locks or row locks depending on storage engine

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

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

Users with fine-grained authorization concept

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