DBMS > H2GIS vs. Quasardb vs. Titan vs. XTDB

System Properties Comparison H2GIS vs. Quasardb vs. Titan vs. XTDB

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Editorial information provided by DB-Engines

Name

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

Spatial extension of H2

Distributed, high-performance timeseries database

Titan is a Graph DBMS optimized for distributed clusters.

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.h2gis.org

quasar.ai

github.com/thinkaurelius/titan

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

Technical documentation

www.h2gis.org/docs/home

doc.quasar.ai/master

github.com/thinkaurelius/titan/wiki

www.xtdb.com/docs

Developer

CNRS

quasardb

Aurelius, owned by DataStax

Juxt Ltd.

Initial release

2013

2009

2012

2019

Current release

3.14.1, January 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache license, version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java

Clojure

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Unix
Windows

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

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST
JDBC

Supported programming languages

Java

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

Clojure
Java
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

yes

via pluggable storage backends

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Source-replica replication with selectable replication factor

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

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

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

Transient mode

User concepts

Access control

yes

based on H2

Cryptographically strong user authentication and audit trail

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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