DBMS > Google BigQuery vs. IBM Cloudant vs. RDFox vs. SAP HANA

System Properties Comparison Google BigQuery vs. IBM Cloudant vs. RDFox vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Database as a Service offering based on Apache CouchDB

High performance knowledge graph and semantic reasoning engine

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

cloud.google.com/bigquery

www.ibm.com/products/cloudant

www.oxfordsemantic.tech

www.sap.com/products/hana.html

Technical documentation

cloud.google.com/bigquery/docs

cloud.ibm.com/docs/Cloudant

docs.oxfordsemantic.tech

help.sap.com/hana

Developer

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oxford Semantic Technologies

SAP

Initial release

2010

2017

2010

Current release

6.0, Septermber 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++

Server operating systems

hosted

Linux
macOS
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions (Map-Reduce) in JavaScript

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

replication via a shared file system

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

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

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

Roles, resources, and access types

yes

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