DBMS > Adabas vs. HugeGraph vs. IBM Cloudant vs. Postgres-XL vs. VoltDB

System Properties Comparison Adabas vs. HugeGraph vs. IBM Cloudant vs. Postgres-XL vs. VoltDB

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

A fast-speed and highly-scalable Graph DBMS

Database as a Service offering based on Apache CouchDB

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

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

github.com/hugegraph
hugegraph.apache.org

www.ibm.com/products/cloudant

www.postgres-xl.org

www.voltdb.com

Technical documentation

hugegraph.apache.org/docs

cloud.ibm.com/docs/Cloudant

www.postgres-xl.org/documentation

docs.voltdb.com

Developer

Software AG

Baidu

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

VoltDB Inc.

Initial release

1971

2018

2010

2014

since 2012, originally named StormDB

2010

Current release

0.9

10 R1, October 2018

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Mozilla public license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Erlang

Java, C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
macOS
Unix

hosted

Linux
macOS

Linux
OS X

for development

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

distributed, parallel query execution

yes

only a subset of SQL 99

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Natural

Groovy
Java
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

in Natural

asynchronous Gremlin script jobs

View functions (Map-Reduce) in JavaScript

user defined functions

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

MVCC

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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)

Users, roles and permissions

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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