DBMS > Hazelcast vs. IBM Db2 warehouse vs. MySQL vs. Quasardb vs. SAP SQL Anywhere

System Properties Comparison Hazelcast vs. IBM Db2 warehouse vs. MySQL vs. Quasardb vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Cloud-based data warehousing service

Widely used open source RDBMS

Distributed, high-performance timeseries database

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

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

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

hazelcast.com

www.ibm.com/products/db2/warehouse

www.mysql.com

quasar.ai

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

hazelcast.org/imdg/docs

dev.mysql.com/doc

doc.quasar.ai/master

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Hazelcast

IBM

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

SAP

formerly Sybase

Initial release

2008

2014

1995

2009

1992

Current release

5.3.6, November 2023

8.4.0, April 2024

3.14.1, January 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

All OS with a Java VM

hosted

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

Import/export of XML data possible

yes

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

SQL-like query language

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

PL/SQL, SQL PL

yes

proprietary syntax

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

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

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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