DBMS > Google BigQuery vs. Hawkular Metrics vs. Virtuoso vs. XTDB

System Properties Comparison Google BigQuery vs. Hawkular Metrics vs. Virtuoso vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine

Document store

Secondary database models

Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	4.27
Rank	#73	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#39	Relational DBMS
	#2	RDF stores
	#9	Search engines

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

cloud.google.com/bigquery

www.hawkular.org

virtuoso.openlinksw.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

cloud.google.com/bigquery/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.openlinksw.com/virtuoso

www.xtdb.com/docs

Developer

Google

Community supported by Red Hat

OpenLink Software

Juxt Ltd.

Initial release

2010

2014

1998

2019

Current release

7.2.11, September 2023

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

MIT License

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

Clojure

Server operating systems

hosted

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

SQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92, SQL-200x, SQL-3, SQLX

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP/JSON API

HTTP REST

ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT

HTTP REST
JDBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Go
Java
Python
Ruby

.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Virtuoso PL

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication

yes, each node contains all data

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
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Competitive advantages

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
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Typical application scenarios

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
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Key customers

Broad use across enterprises and governments including — European Union (EU) US Government...
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Market metrics

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
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Licensing and pricing models

Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
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