DBMS > HEAVY.AI vs. MariaDB vs. Microsoft SQL Server vs. Sadas Engine vs. SpatiaLite

System Properties Comparison HEAVY.AI vs. MariaDB vs. Microsoft SQL Server vs. Sadas Engine vs. SpatiaLite

Editorial information provided by DB-Engines

Name

Description

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

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Microsofts flagship relational DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Spatial extension of SQLite

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

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

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

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

www.sadasengine.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.heavy.ai

mariadb.com/kb/en/library

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

HEAVY.AI, Inc.

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Microsoft

SADAS s.r.l.

Alessandro Furieri

Initial release

2016

2009

Fork of MySQL, which was first released in 1995

1989

2006

2008

Current release

5.10, January 2022

11.3.2, February 2024

SQL Server 2022, November 2022

8.0

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version 2, commercial enterprise subscription available

commercial

restricted free version is available

commercial

free trial version available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

C++ and CUDA

C and C++

C++

Server operating systems

Linux

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
Windows

AIX
Linux
Windows

server-less

Data scheme

yes

Dynamic columns are supported

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
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
Proprietary native API

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

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

PL/SQL compatibility added with version 10.3

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

several options for horizontal partitioning and Sharding

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

none

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

not for MyISAM storage engine

yes

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

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

In-memory capabilities

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

yes

with MEMORY storage engine

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

MariaDB is the most powerful open source relational database – modern SQL and JSON...
» more

Competitive advantages

MariaDB Servers have many features unavailable in other open source relational databases....
» more

Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
» more

Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
» more

Market metrics

MariaDB is the default database in the LAMP stack supplied by Red Hat and SUSE Linux,...
» more

Licensing and pricing models

MariaDB plc subscriptions cover our free, open source database, Community Server,...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.