DBMS > Google BigQuery vs. RavenDB vs. RDFox vs. TempoIQ

System Properties Comparison Google BigQuery vs. RavenDB vs. RDFox vs. TempoIQ

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service with append-only tables

Open Source Operational and Transactional Enterprise NoSQL Document Database

High performance knowledge graph and semantic reasoning engine

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Relational DBMS

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

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Website

cloud.google.com/bigquery

ravendb.net

www.oxfordsemantic.tech

tempoiq.com (offline)

Technical documentation

cloud.google.com/bigquery/docs

ravendb.net/docs

docs.oxfordsemantic.tech

Developer

Google

Hibernating Rhinos

Oxford Semantic Technologies

TempoIQ

Initial release

2010

2017

2012

Current release

5.4, July 2022

6.0, Septermber 2022

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

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

C++

Server operating systems

hosted

Linux
macOS
Raspberry Pi
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

RDF schemas

schema-free

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

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP/JSON API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
Java

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID, Cluster-wide transaction available

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

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

Google Cloud Identity & Access Management (IAM)

Authorization levels configured per client per database

Roles, resources, and access types

simple authentication-based access control

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.