DBMS > AnzoGraph DB vs. mSQL vs. OrigoDB vs. Prometheus

System Properties Comparison AnzoGraph DB vs. mSQL vs. OrigoDB vs. Prometheus

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

Open-source Time Series DBMS and monitoring system

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	7.92
Rank	#51	Overall
	#2	Time Series DBMS

Website

cambridgesemantics.com/anzograph

hughestech.com.au/products/msql

origodb.com

prometheus.io

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

origodb.com/docs

prometheus.io/docs

Developer

Cambridge Semantics

Hughes Technologies

Robert Friberg et al

Initial release

2018

1994

2009

under the name LiveDB

2015

Current release

2.3, January 2021

4.4, October 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

free licenses can be provided

Open Source

Apache 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.

Implementation language

Server operating systems

Linux

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

Linux
Windows

Data scheme

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

Numeric data only

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 of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

A subset of ANSI SQL is implemented

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

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
ODBC

.NET Client API
HTTP API
LINQ

RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Source-replica replication

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Foreign keys

Referential integrity

not needed in graphs

depending on model

Transaction concepts

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

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

Access rights for users and roles

Role based authorization

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