DBMS > Drizzle vs. HEAVY.AI vs. MaxDB vs. Microsoft SQL Server

System Properties Comparison Drizzle vs. HEAVY.AI vs. MaxDB vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A robust and reliable RDBMS optimized to run all major SAP solutions

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

maxdb.sap.com

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

Technical documentation

docs.heavy.ai

maxdb.sap.com/documentation

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

Developer

Drizzle project, originally started by Brian Aker

HEAVY.AI, Inc.

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Initial release

2008

2016

1984

1989

Current release

7.2.4, September 2012

5.10, January 2022

7.9.10.12, February 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache Version 2; enterprise edition available

commercial

Limited community edition free

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++ and CUDA

C++

Server operating systems

FreeBSD
Linux
OS X

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
WebDAV

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

Supported programming languages

C
C++
Java
PHP

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C#
Java
Perl
PHP
Python

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

Server-side scripts

Stored procedures

yes

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

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Source-replica replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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