DBMS > Drizzle vs. Hive vs. MariaDB vs. Quasardb vs. Titan

System Properties Comparison Drizzle vs. Hive vs. MariaDB vs. Quasardb vs. Titan

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.

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

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

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.

Distributed, high-performance timeseries database

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Time Series DBMS

Graph 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	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

quasar.ai

github.com/thinkaurelius/titan

Technical documentation

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

mariadb.com/kb/en/library

doc.quasar.ai/master

github.com/thinkaurelius/titan/wiki

Developer

Drizzle project, originally started by Brian Aker

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

quasardb

Aurelius, owned by DataStax

Initial release

2008

2012

2009

Fork of MySQL, which was first released in 1995

2009

2012

Current release

7.2.4, September 2012

3.1.3, April 2022

11.3.2, February 2024

3.14.1, January 2024

License

Commercial or Open Source

Open Source

GNU GPL

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

Open Source

Apache license, version 2.0

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.

STACKIT MariaDB offers MariaDB in a fully managed version in enterprise grade, 100% GDPR-compliant.

Implementation language

C++

Java

C and C++

C++

Java

Server operating systems

FreeBSD
Linux
OS X

All OS with a Java VM

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

BSD
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

Dynamic columns are supported

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

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C++
Java
PHP

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

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

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

PL/SQL compatibility added with version 10.3

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

several options for horizontal partitioning and Sharding

Sharding

consistent hashing

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Relationships in graph

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

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Key customers

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Market metrics

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