DBMS > BigObject vs. Blueflood vs. OrigoDB vs. Titan

System Properties Comparison BigObject vs. Blueflood vs. OrigoDB vs. Titan

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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

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

A fully ACID in-memory object graph database

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Document store
Object oriented DBMS

Graph DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

bigobject.io

blueflood.io

origodb.com

github.com/thinkaurelius/titan

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

origodb.com/docs

github.com/thinkaurelius/titan/wiki

Developer

BigObject, Inc.

Rackspace

Robert Friberg et al

Aurelius, owned by DataStax

Initial release

2015

2013

2009

under the name LiveDB

2012

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 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

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Implementation language

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

predefined scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST

.NET Client API
HTTP API
LINQ

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net

Clojure
Java
Python

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

depending on model

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

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

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

show all

Recent citations in the news

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

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

Beyond Titan: The Evolution of DataStax's New Graph Database
21 June 2016, Datanami

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

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
9 November 2013, Center for Data Innovation

provided by Google News

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