DBMS > Adabas vs. Apache Jena - TDB vs. Google BigQuery vs. Lovefield vs. Postgres-XL

System Properties Comparison Adabas vs. Apache Jena - TDB vs. Google BigQuery vs. Lovefield vs. Postgres-XL

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 RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

Large scale data warehouse service with append-only tables

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Multivalue DBMS

RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	3.85
Rank	#86	Overall
	#3	RDF stores

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Website

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

jena.apache.org/documentation/tdb/index.html

cloud.google.com/bigquery

google.github.io/lovefield

www.postgres-xl.org

Technical documentation

jena.apache.org/documentation/tdb/index.html

cloud.google.com/bigquery/docs

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

www.postgres-xl.org/documentation

Developer

Software AG

Apache Software Foundation

originally developed by HP Labs

Google

Initial release

1971

2000

2010

2014

since 2012, originally named StormDB

Current release

4.9.0, July 2023

2.1.12, February 2017

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

commercial

Open Source

Apache 2.0

Open Source

Mozilla public license

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

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM

hosted

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Data scheme

yes

RDF Schemas

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like query language

via JavaScript builder pattern

yes

distributed, parallel query execution

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

RESTful HTTP/JSON API

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

Supported programming languages

Natural

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

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

Server-side scripts

Stored procedures

in Natural

yes

user defined functions

in JavaScript

user defined functions

Triggers

yes

via event handler

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

Since BigQuery is designed for querying data

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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)

Access control via Jena Security

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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