DBMS > MySQL vs. Quasardb vs. TimescaleDB vs. TimesTen vs. Tkrzw

System Properties Comparison MySQL vs. Quasardb vs. TimescaleDB vs. TimesTen vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

Distributed, high-performance timeseries database

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

In-Memory RDBMS compatible to Oracle

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.mysql.com

quasar.ai

www.timescale.com

www.oracle.com/database/technologies/related/timesten.html

dbmx.net/tkrzw

Technical documentation

dev.mysql.com/doc

doc.quasar.ai/master

docs.timescale.com

docs.oracle.com/database/timesten-18.1

Developer

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

Timescale

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Mikio Hirabayashi

Initial release

1995

2009

2017

1998

2020

Current release

8.3.0, January 2024

3.14.1, January 2024

2.13.0, November 2023

11 Release 2 (11.2.2.8.0)

0.9.3, August 2020

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

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

Open Source

Apache 2.0

commercial

Open Source

Apache 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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 query language

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
C++
Java
PL/SQL

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

Source-replica replication with hot standby and reads on replicas

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

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

yes

Transient mode

yes

using specific database classes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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