DBMS > Adabas vs. Geode vs. Google BigQuery vs. HyperSQL vs. Microsoft Azure AI Search

System Properties Comparison Adabas vs. Geode vs. Google BigQuery vs. HyperSQL vs. Microsoft Azure AI Search

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Large scale data warehouse service with append-only tables

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Search-as-a-service for web and mobile app development

Primary database model

Secondary database models

Vector DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Website

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

geode.apache.org

cloud.google.com/bigquery

hsqldb.org

azure.microsoft.com/en-us/services/search

Technical documentation

geode.apache.org/docs

cloud.google.com/bigquery/docs

hsqldb.org/web/hsqlDocsFrame.html

learn.microsoft.com/en-us/azure/search

Developer

Software AG

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

Microsoft

Initial release

1971

2002

2010

2001

2015

Current release

1.1, February 2017

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

based on BSD license

commercial

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

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM

the JDK (8 or later) is also required

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language (OQL)

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

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Natural

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

Java, SQL

Triggers

yes

Cache Event Listeners

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

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

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

User concepts

Access control

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

Access rights per client and object definable

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

using Azure authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.