DBMS > mSQL vs. PlanetScale vs. Prometheus vs. RDF4J

System Properties Comparison mSQL vs. PlanetScale vs. Prometheus vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

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

Open-source Time Series DBMS and monitoring system

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Time Series DBMS

RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	1.09
Rank	#178	Overall
	#82	Relational DBMS

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

hughestech.com.au/products/msql

planetscale.com

prometheus.io

rdf4j.org

Technical documentation

planetscale.com/docs

prometheus.io/docs

rdf4j.org/documentation

Developer

Hughes Technologies

PlanetScale

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

1994

2020

2015

2004

Current release

4.4, October 2021

License

Commercial or Open Source

commercial

free licenses can be provided

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java

Server operating systems

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

Docker
Linux
macOS

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency across shards
Immediate Consistency within a shard

none

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID at shard level

ACID

Isolation support depends on the API used

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

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

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