DBMS > mSQL vs. OrigoDB vs. RocksDB vs. Stardog vs. TimescaleDB

System Properties Comparison mSQL vs. OrigoDB vs. RocksDB vs. Stardog vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Key-value store

Graph DBMS
RDF store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

hughestech.com.au/products/msql

Technical documentation

origodb.com/docs

github.com/facebook/rocksdb/wiki

docs.stardog.com

docs.timescale.com

Developer

Hughes Technologies

Robert Friberg et al

Facebook, Inc.

Stardog-Union

Timescale

Initial release

1994

2009

under the name LiveDB

2013

2010

2017

Current release

4.4, October 2021

8.11.4, April 2024

7.3.0, May 2020

2.15.0, May 2024

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

BSD

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

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

Linux
Windows

Linux

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

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.

can be achieved using .NET

Import/export of XML data possible

yes

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

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

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC

.NET Client API
HTTP API
LINQ

C++ API
Java API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

C
C++
Go
Java
Perl
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and aggregates, HTTP Server extensions in Java

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

Domain Events

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Multi-source replication in HA-Cluster

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

relationships in graphs

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

User concepts

Access control

Role based authorization

Access rights for users and roles

fine grained access rights according to SQL-standard

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