DBMS > Amazon Neptune vs. Ingres vs. Microsoft SQL Server vs. Sadas Engine vs. SQLite

System Properties Comparison Amazon Neptune vs. Ingres vs. Microsoft SQL Server vs. Sadas Engine vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Well established RDBMS

Microsofts flagship relational DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/neptune

www.actian.com/databases/ingres

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

www.sadasengine.com

www.sqlite.org

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.actian.com/ingres

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.sqlite.org/docs.html

Developer

Amazon

Actian Corporation

Microsoft

SADAS s.r.l.

Dwayne Richard Hipp

Initial release

2017

1974

originally developed at University Berkely in early 1970s

1989

2006

2000

Current release

11.2, May 2022

SQL Server 2022, November 2022

8.0

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free trial version available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

AIX
Linux
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

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

JDBC
ODBC
Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Ingres Replicator

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

via file-system locks

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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