DBMS > Amazon Aurora vs. AnzoGraph DB vs. Hazelcast vs. MySQL vs. ObjectBox

System Properties Comparison Amazon Aurora vs. AnzoGraph DB vs. Hazelcast vs. MySQL vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

A widely adopted in-memory data grid

Widely used open source RDBMS

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Key/Value like access via memcached API

Object oriented DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

Time Series DBMS

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

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

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

aws.amazon.com/rds/aurora

cambridgesemantics.com/anzograph

hazelcast.com

www.mysql.com

objectbox.io

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

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

hazelcast.org/imdg/docs

dev.mysql.com/doc

docs.objectbox.io

Developer

Amazon

Cambridge Semantics

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

ObjectBox Limited

Initial release

2015

2018

2008

1995

2017

Current release

2.3, January 2021

5.3.6, November 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Java

C and C++

Server operating systems

hosted

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

schema-free

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

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

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

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

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary native API

Supported programming languages

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

C++
Java
Python

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

yes

Event Listeners, Executor Services

yes

proprietary syntax

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Automatic sharding

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication in MPP-Cluster

yes

Replicated Map

Multi-source replication
Source-replica replication

online/offline synchronization between client and server

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

fine grained access rights according to SQL-standard

Access rights for users and roles

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

yes

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