DBMS > Drizzle vs. Lovefield vs. Titan vs. Virtuoso

System Properties Comparison Drizzle vs. Lovefield vs. Titan vs. Virtuoso

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Embeddable relational database for web apps written in pure JavaScript

Titan is a Graph DBMS optimized for distributed clusters.

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

Primary database model

Relational DBMS

Graph DBMS

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

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	4.26
Rank	#78	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#42	Relational DBMS
	#2	RDF stores
	#9	Search engines

Website

google.github.io/lovefield

github.com/thinkaurelius/titan

virtuoso.openlinksw.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

github.com/thinkaurelius/titan/wiki

docs.openlinksw.com/virtuoso

Developer

Drizzle project, originally started by Brian Aker

Google

Aurelius, owned by DataStax

OpenLink Software

Initial release

2008

2014

2012

1998

Current release

7.2.4, September 2012

2.1.12, February 2017

7.2.11, September 2023

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

Apache license, version 2.0

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

JavaScript

Java

Server operating systems

FreeBSD
Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Unix
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

via JavaScript builder pattern

yes

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

APIs and other access methods

JDBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

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

Supported programming languages

C
C++
Java
PHP

JavaScript

Clojure
Java
Python

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

Server-side scripts

Stored procedures

yes

Virtuoso PL

Triggers

hooks for callbacks inside the server can be used.

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

via pluggable storage backends

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

User authentification and security via Rexster Graph Server

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...
» more

Competitive advantages

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more

Typical application scenarios

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more

Key customers

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

Market metrics

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more

Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Recent citations in the news

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

5 Q's with Graph Database Expert Marko Rodriguez – Center for Data Innovation
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provided by Google News

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