DBMS > PlanetScale vs. Quasardb vs. SQLite vs. TimescaleDB vs. VictoriaMetrics

System Properties Comparison PlanetScale vs. Quasardb vs. SQLite vs. TimescaleDB vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Distributed, high-performance timeseries database

Widely used embeddable, in-process RDBMS

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

Technical documentation

planetscale.com/docs

doc.quasar.ai/master

www.sqlite.org/docs.html

docs.timescale.com

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

PlanetScale

quasardb

Dwayne Richard Hipp

Timescale

VictoriaMetrics

Initial release

2020

2009

2000

2017

2018

Current release

3.14.1, January 2024

3.46.0 (23 May 2024), May 2024

2.15.0, May 2024

v1.91, May 2023

License

Commercial or Open Source

commercial

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

Open Source

Public Domain

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

C++

Server operating systems

Docker
Linux
macOS

BSD
Linux
OS X
Windows

server-less

Linux
OS X
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

integer and binary

yes

not rigid because of 'dynamic typing' concept.

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

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

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

none

Source-replica replication with hot standby and reads on replicas

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Eventual 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 at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

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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