DBMS > Adabas vs. Amazon DynamoDB vs. EsgynDB vs. Google Cloud Firestore vs. Teradata

System Properties Comparison Adabas vs. Amazon DynamoDB vs. EsgynDB vs. Google Cloud Firestore vs. Teradata

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

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.

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Multivalue DBMS

Document store
Key-value store

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series 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	7.85
Rank	#51	Overall
	#8	Document stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

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

aws.amazon.com/dynamodb

www.esgyn.cn

firebase.google.com/products/firestore

www.teradata.com

Technical documentation

docs.aws.amazon.com/dynamodb

firebase.google.com/docs/firestore

docs.teradata.com

Developer

Software AG

Amazon

Esgyn

Google

Teradata

Initial release

1971

2012

2015

2017

1984

Current release

Teradata Vantage 1.0 MU2, January 2019

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

hosted
Linux

Data scheme

yes

schema-free

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL 2016 + extensions

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

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

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Natural

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

by integration with AWS Lambda

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

Sharding

Hashing

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

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

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

ACID

yes

ACID

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)

fine grained access rights according to SQL-standard

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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