DBMS > Microsoft SQL Server vs. Newts vs. OrigoDB

System Properties Comparison Microsoft SQL Server vs. Newts vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Time Series DBMS based on Cassandra

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	824.29
Rank	#3	Overall
	#3	Relational 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

www.microsoft.com/en-us/sql-server

opennms.github.io/newts

origodb.com

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

github.com/OpenNMS/newts/wiki

origodb.com/docs

Developer

Microsoft

OpenNMS Group

Robert Friberg et al

Initial release

1989

2014

2009

under the name LiveDB

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

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

Linux
Windows

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST
Java API

.NET Client API
HTTP API
LINQ

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java

.Net

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

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

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

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

fine grained access rights according to SQL-standard

Role based authorization

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