DBMS > Adabas vs. Amazon Aurora vs. Apache Druid vs. OrientDB vs. RocksDB

System Properties Comparison Adabas vs. Amazon Aurora vs. Apache Druid 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

MySQL and PostgreSQL compatible cloud service by Amazon

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

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

Primary database model

Multivalue DBMS

Relational DBMS

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store

Key-value store

Secondary database models

Document store

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series 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

aws.amazon.com/rds/aurora

druid.apache.org

orientdb.org

rocksdb.org

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

druid.apache.org/docs/latest/design

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

github.com/facebook/rocksdb/wiki

Developer

Software AG

Amazon

Apache Software Foundation and contributors

OrientDB LTD; CallidusCloud; SAP

Facebook, Inc.

Initial release

1971

2015

2012

2010

2013

Current release

29.0.1, April 2024

3.2.29, March 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache license v2

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Unix

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

Linux

Data scheme

yes

schema-less columns are supported

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL for querying

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

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP/JSON API

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

C++ API
Java API

Supported programming languages

Natural

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.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

yes

Java, Javascript

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

yes, via HDFS, S3 or other storage engines

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

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)

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles; record level security configurable

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