DBMS > Microsoft Azure SQL Database vs. Microsoft Azure Table Storage vs. NSDb vs. OrigoDB vs. SQLite

System Properties Comparison Microsoft Azure SQL Database vs. Microsoft Azure Table Storage vs. NSDb vs. OrigoDB vs. SQLite

Editorial information provided by DB-Engines

Name

Description

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

A Wide Column Store for rapid development using massive semi-structured datasets

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

A fully ACID in-memory object graph database

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Wide column store

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

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

azure.microsoft.com/en-us/services/storage/tables

nsdb.io

origodb.com

www.sqlite.org

Technical documentation

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

nsdb.io/Architecture

origodb.com/docs

www.sqlite.org/docs.html

Developer

Microsoft

Robert Friberg et al

Dwayne Richard Hipp

Initial release

2010

2012

2017

2009

under the name LiveDB

2000

Current release

V12

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Public Domain

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, Scala

Server operating systems

hosted

Linux
macOS

Linux
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

Java
Scala

.Net

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

Access rights based on private key authentication or shared access signatures

Role based authorization

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