DBMS > Hive vs. MariaDB vs. Microsoft Azure Synapse Analytics vs. Quasardb

System Properties Comparison Hive vs. MariaDB vs. Microsoft Azure Synapse Analytics vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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.

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

hive.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

azure.microsoft.com/services/synapse-analytics

quasar.ai

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

mariadb.com/kb/en/library

docs.microsoft.com/azure/synapse-analytics

doc.quasar.ai/master

Developer

Apache Software Foundation

initially developed by Facebook

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

The lead developer Monty Widenius is the original author of MySQL

Microsoft

quasardb

Initial release

2012

2009

Fork of MySQL, which was first released in 1995

2016

2009

Current release

3.1.3, April 2022

11.3.2, February 2024

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL version 2, commercial enterprise subscription available

commercial

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

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C and C++

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

hosted

BSD
Linux
OS X
Windows

Data scheme

yes

Dynamic columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

C++
Java
PHP
Python

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

C#
Java
PHP

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

Sharding, horizontal partitioning

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

yes

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

by using LevelDB

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

Transient mode

User concepts

Access control

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes

Cryptographically strong user authentication and audit trail

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

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