DBMS > Adabas vs. EsgynDB vs. Firebase Realtime Database vs. Google BigQuery vs. H2GIS

System Properties Comparison Adabas vs. EsgynDB vs. Firebase Realtime Database vs. Google BigQuery vs. H2GIS

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

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Large scale data warehouse service with append-only tables

Spatial extension of H2

Primary database model

Secondary database models

Relational DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

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

www.esgyn.cn

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

www.h2gis.org

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

www.h2gis.org/docs/home

Developer

Software AG

Esgyn

Google

acquired by Google 2014

Google

CNRS

Initial release

1971

2015

2012

2010

2013

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

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

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

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.

Secondary indexes

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

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

Natural

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

limited functionality with using 'rules'

user defined functions

in JavaScript

yes

based on H2

Triggers

Callbacks are triggered when data changes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication between multi datacenters

yes

based on H2

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (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.

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

based on H2

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