DBMS > Adabas vs. Amazon SimpleDB vs. Google Cloud Firestore vs. Microsoft SQL Server vs. RocksDB

System Properties Comparison Adabas vs. Amazon SimpleDB vs. Google Cloud Firestore vs. Microsoft SQL Server vs. RocksDB

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

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Microsofts flagship relational DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

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

aws.amazon.com/simpledb

firebase.google.com/products/firestore

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

rocksdb.org

Technical documentation

docs.aws.amazon.com/simpledb

firebase.google.com/docs/firestore

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

github.com/facebook/rocksdb/wiki

Developer

Software AG

Amazon

Google

Microsoft

Facebook, Inc.

Initial release

1971

2007

2017

1989

2013

Current release

SQL Server 2022, November 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

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

All columns are indexed automatically

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

RESTful HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

C++ API
Java API

Supported programming languages

Natural

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

in Natural

yes, Firebase Rules & Cloud Functions

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

Triggers

yes, with Cloud Functions

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 must be implemented in the application

Sharding

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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