DBMS > Adabas vs. Amazon DynamoDB vs. EsgynDB vs. Google Cloud Datastore vs. Ingres

System Properties Comparison Adabas vs. Amazon DynamoDB vs. EsgynDB vs. Google Cloud Datastore vs. Ingres

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, scalable database service by Amazon with the data stored in Amazons cloud

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Well established RDBMS

Primary database model

Multivalue DBMS

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Website

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

aws.amazon.com/dynamodb

www.esgyn.cn

cloud.google.com/datastore

www.actian.com/databases/ingres

Technical documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/datastore/docs

docs.actian.com/ingres

Developer

Software AG

Amazon

Esgyn

Google

Actian Corporation

Initial release

1971

2012

2015

2008

1974

originally developed at University Berkely in early 1970s

Current release

11.2, May 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

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

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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.

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

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like query language (GQL)

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

ADO.NET
JDBC
ODBC

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

Natural

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

using Google App Engine

yes

Triggers

yes

by integration with AWS Lambda

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Multi-source replication between multi datacenters

Multi-source replication using Paxos

Ingres Replicator

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

using Google 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

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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.

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)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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