DBMS > Adabas vs. Google BigQuery vs. Greenplum vs. Hypertable vs. Realm

System Properties Comparison Adabas vs. Google BigQuery vs. Greenplum vs. Hypertable vs. Realm

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Large scale data warehouse service with append-only tables

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

An open source BigTable implementation based on distributed file systems such as Hadoop

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

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

cloud.google.com/bigquery

greenplum.org

realm.io

Technical documentation

cloud.google.com/bigquery/docs

docs.greenplum.org

realm.io/docs

Developer

Software AG

Google

Pivotal Software Inc.

Hypertable Inc.

Realm, acquired by MongoDB in May 2019

Initial release

1971

2010

2005

2009

2014

Current release

7.0.0, September 2023

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

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

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Android
Backend: server-less
iOS
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

since Version 4.2

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP/JSON API

JDBC
ODBC

C++ API
Thrift

Supported programming languages

Natural

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
Java
Perl
Python
R

C++
Java
Perl
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Since BigQuery is designed for querying data

ACID

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

In-Memory realm

User concepts

Access control

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

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

yes

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