DBMS > Google BigQuery vs. NuoDB vs. RDF4J

System Properties Comparison Google BigQuery vs. NuoDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

NuoDB is a webscale distributed database that supports SQL and ACID transactions

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

RDF store

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Trend Chart

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	0.99
Rank	#195	Overall
	#92	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

cloud.google.com/bigquery

www.3ds.com/nuodb-distributed-sql-database

rdf4j.org

Technical documentation

cloud.google.com/bigquery/docs

doc.nuodb.com

rdf4j.org/documentation

Developer

Google

Dassault Systèmes

originally NuoDB, Inc.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2010

2013

2004

License

Commercial or Open Source

commercial

limited edition free

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

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

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Managed transparently by NuoDB

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

Since BigQuery is designed for querying data

ACID

tunable commit protocol

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Temporary table

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Standard SQL roles/ privileges, Administrative Users

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