DBMS > Google BigQuery vs. HyperSQL vs. MaxDB vs. OrigoDB vs. SAP IQ

System Properties Comparison Google BigQuery vs. HyperSQL vs. MaxDB vs. OrigoDB vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A robust and reliable RDBMS optimized to run all major SAP solutions

A fully ACID in-memory object graph database

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

column-oriented

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

cloud.google.com/bigquery

hsqldb.org

maxdb.sap.com

origodb.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

cloud.google.com/bigquery/docs

hsqldb.org/web/hsqlDocsFrame.html

maxdb.sap.com/documentation

origodb.com/docs

help.sap.com/docs/SAP_IQ

Developer

Google

SAP, acquired from Software AG (Adabas-D) in 1997

Robert Friberg et al

SAP, formerly Sybase

Initial release

2010

2001

1984

2009

under the name LiveDB

1994

Current release

2.7.2, June 2023

7.9.10.12, February 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

Limited community edition free

Open Source

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

C++

Server operating systems

hosted

All OS with a Java VM

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

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

.Net
C#
Java
Perl
PHP
Python

.Net

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java, SQL

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

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

Role based authorization

fine grained access rights according to SQL-standard

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