DBMS > Adabas vs. Ehcache vs. HugeGraph vs. Lovefield vs. PostgreSQL

System Properties Comparison Adabas vs. Ehcache vs. HugeGraph vs. Lovefield vs. PostgreSQL

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 widely adopted Java cache with tiered storage options

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

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

www.ehcache.org

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

www.postgresql.org

Technical documentation

www.ehcache.org/documentation

hugegraph.apache.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

www.postgresql.org/docs

Developer

Software AG

Terracotta Inc, owned by Software AG

Baidu

Google

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

1971

2009

2018

2014

1989

1989: Postgres, 1996: PostgreSQL

Current release

3.10.0, March 2022

0.9

2.1.12, February 2017

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM

Linux
macOS
Unix

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

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

specific XML-type available, 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

SQL-like query language

via JavaScript builder pattern

yes

standard with numerous 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

JCache

Java API
RESTful HTTP API
TinkerPop Gremlin

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

Supported programming languages

Natural

Java

Groovy
Java
Python

JavaScript

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

in Natural

asynchronous Gremlin script jobs

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Cache Event Listeners

Using read-only observers

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

by using Terracotta Server

yes

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

none

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

by using Terracotta Server

yes

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

none

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

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

Users, roles and permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

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