DBMS > Amazon Neptune vs. Microsoft SQL Server vs. OpenEdge vs. OrientDB vs. Realm

System Properties Comparison Amazon Neptune vs. Microsoft SQL Server vs. OpenEdge vs. OrientDB vs. Realm

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Microsofts flagship relational DBMS

Application development environment with integrated database management system

Multi-model DBMS (Document, Graph, Key/Value)

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Graph DBMS
Key-value store

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

aws.amazon.com/neptune

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

www.progress.com/openedge

orientdb.org

realm.io

Technical documentation

aws.amazon.com/neptune/developer-resources

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

documentation.progress.com/output/ua/OpenEdge_latest

www.orientdb.com/docs/last/index.html

realm.io/docs

Developer

Amazon

Microsoft

Progress Software Corporation

OrientDB LTD; CallidusCloud; SAP

Realm, acquired by MongoDB in May 2019

Initial release

2017

1989

1984

2010

2014

Current release

SQL Server 2022, November 2022

OpenEdge 12.2, March 2020

3.2.29, March 2024

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache version 2

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

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like query language, no joins

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

JDBC
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

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

Progress proprietary ABL (Advanced Business Language)

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

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

yes

Java, Javascript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Hooks

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

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

horizontal partitioning

since Version 11.4

Sharding

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.

yes, but depending on the SQL-Server Edition

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationship in graphs

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

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

In-Memory realm

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

Users and groups

Access rights for users and roles; record level security configurable

yes

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