DBMS > Hazelcast vs. Microsoft SQL Server vs. MonetDB vs. SAP SQL Anywhere

System Properties Comparison Hazelcast vs. Microsoft SQL Server vs. MonetDB vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

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

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

hazelcast.com

www.microsoft.com/en-us/sql-server

www.monetdb.org

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

Technical documentation

hazelcast.org/imdg/docs

learn.microsoft.com/en-US/sql/sql-server

www.monetdb.org/Documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Hazelcast

Microsoft

MonetDB BV

SAP

formerly Sybase

Initial release

2008

1989

2004

1992

Current release

5.3.6, November 2023

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

SQL-like query language

yes

SQL 2003 with some extensions

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, in SQL, C, R

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

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Transaction concepts

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

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Role-based access control

fine grained access rights according to SQL-standard

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