DBMS > DataFS vs. Microsoft Azure SQL Database vs. Newts vs. NSDb vs. OrigoDB

System Properties Comparison DataFS vs. Microsoft Azure SQL Database vs. Newts vs. NSDb vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Database as a Service offering with high compatibility to Microsoft SQL Server

Time Series DBMS based on Cassandra

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

Primary database model

Object oriented DBMS

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Secondary database models

Graph DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Website

newdatabase.com

azure.microsoft.com/en-us/products/azure-sql/database

opennms.github.io/newts

nsdb.io

origodb.com

Technical documentation

dev.mobiland.com/Overview.xsp

docs.microsoft.com/en-us/azure/azure-sql

github.com/OpenNMS/newts/wiki

nsdb.io/Architecture

origodb.com/docs

Developer

Mobiland AG

Microsoft

OpenNMS Group

Robert Friberg et al

Initial release

2018

2010

2014

2017

2009

under the name LiveDB

Current release

1.1.263, October 2022

V12

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

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++

Java

Java, Scala

Server operating systems

Windows

hosted

Linux
OS X
Windows

Linux
macOS

Linux
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

HTTP REST
Java API

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java

Java
Scala

.Net

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

no, except callback-events from server when changes happened

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

based on Cassandra

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

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

Using Apache Lucene

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

Windows-Profile

fine grained access rights according to SQL-standard

Role based authorization

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