DBMS > Apache Phoenix vs. Titan

System Properties Comparison Apache Phoenix vs. Titan

Please select another system to include it in the comparison.

Our visitors often compare Apache Phoenix and Titan with PostgreSQL, Elasticsearch and ClickHouse.

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

A scale-out RDBMS with evolutionary schema built on Apache HBase

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Graph DBMS

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

Score	1.82
Rank	#124	Overall
	#60	Relational DBMS

Website

phoenix.apache.org

github.com/thinkaurelius/titan

Technical documentation

phoenix.apache.org

github.com/thinkaurelius/titan/wiki

Developer

Apache Software Foundation

Aurelius, owned by DataStax

Initial release

2014

2012

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache license, version 2.0

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

Server operating systems

Linux
Unix
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

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

JDBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual 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

Durability

Support for making data persistent

yes

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

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 Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

User authentification and security via Rexster Graph Server

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

show all

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

show all

Recent citations in the news

Bridge the SQL-NoSQL gap with Apache Phoenix
9 July 2024, InfoWorld

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix
2 June 2016, Amazon Web Services

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, Microsoft Azure

Hortonworks Starts Hadoop Summit with Data Platform Update
28 June 2016, ADTmag

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps
2 June 2016, Amazon Web Services

provided by Google News

DataStax Acquires Aurelius and its TitanDB Graph Database
31 May 2024, Data Center Knowledge

Building a Graph Database on AWS Using Amazon DynamoDB and Titan
22 October 2015, Amazon Web Services

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

Performance Tuning Your Titan Graph Database on AWS
14 December 2015, Amazon Web Services

The continuing rise of graph databases
15 May 2017, ZDNet

provided by Google News

Share this page