DBMS > Adabas vs. Firebase Realtime Database vs. Hive vs. OrientDB vs. RocksDB

System Properties Comparison Adabas vs. Firebase Realtime Database vs. Hive vs. OrientDB 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

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Multivalue DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store

Key-value store

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

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

Website

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

firebase.google.com/products/realtime-database

hive.apache.org

orientdb.org

rocksdb.org

Technical documentation

firebase.google.com/docs/database

cwiki.apache.org/confluence/display/Hive/Home

www.orientdb.com/docs/last/index.html

github.com/facebook/rocksdb/wiki

Developer

Software AG

Google

acquired by Google 2014

Apache Software Foundation

initially developed by Facebook

OrientDB LTD; CallidusCloud; SAP

Facebook, Inc.

Initial release

1971

2012

2010

2013

Current release

3.1.3, April 2022

3.2.29, March 2024

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

All OS with a Java VM

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

yes

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

SQL-like query language, no joins

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Thrift

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

Natural

Java
JavaScript
Objective-C

C++
Java
PHP
Python

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

in Natural

limited functionality with using 'rules'

yes

user defined functions and integration of map-reduce

Java, Javascript

Triggers

Callbacks are triggered when data changes

Hooks

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

could be achieved with distributed queries

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

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

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)

yes, based on authentication and database rules

Access rights for users, groups and roles

Access rights for users and roles; record level security configurable

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