DBMS > Adabas vs. Amazon Neptune vs. GridGain vs. Microsoft SQL Server vs. NuoDB

System Properties Comparison Adabas vs. Amazon Neptune vs. GridGain vs. Microsoft SQL Server vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Fast, reliable graph database built for the cloud

GridGain is an in-memory computing platform, built on Apache Ignite

Microsofts flagship relational DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Multivalue DBMS

Graph DBMS
RDF store

Key-value store
Relational 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	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

aws.amazon.com/neptune

www.gridgain.com

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

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

aws.amazon.com/neptune/developer-resources

www.gridgain.com/docs/index.html

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

doc.nuodb.com

Developer

Software AG

Amazon

GridGain Systems, Inc.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Initial release

1971

2017

2007

1989

2013

Current release

GridGain 8.5.1

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

limited edition free

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, C++, .Net

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

yes

schema-free

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

with add-on product Adabas SQL Gateway

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

ADO.NET
JDBC
ODBC

Supported programming languages

Natural

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

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

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

Server-side scripts

Stored procedures

in Natural

yes (compute grid and cache interceptors can be used instead)

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

Java, SQL

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

none

Sharding

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

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

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 (replicated cache)

yes, but depending on the SQL-Server Edition

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

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