DBMS > Blueflood vs. Heroic vs. SAP IQ vs. Titan

System Properties Comparison Blueflood vs. Heroic vs. SAP IQ 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

Scalable TimeSeries DBMS based on Cassandra

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Columnar RDBMS optimized for Big Data analytics

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Time Series DBMS

Relational DBMS

column-oriented

Graph DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

blueflood.io

github.com/spotify/heroic

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

github.com/thinkaurelius/titan

Technical documentation

github.com/rax-maas/blueflood/wiki

spotify.github.io/heroic

help.sap.com/docs/SAP_IQ

github.com/thinkaurelius/titan/wiki

Developer

Rackspace

Spotify

SAP, formerly Sybase

Aurelius, owned by DataStax

Initial release

2013

2014

1994

2012

Current release

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

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
OS X

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

predefined scheme

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

SAP/Sybase Replication Server

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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

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7 September 2016, InfoWorld

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