DBMS > Heroic vs. Kdb vs. TempoIQ vs. Titan

System Properties Comparison Heroic vs. Kdb vs. TempoIQ vs. Titan

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed 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

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

High performance Time Series DBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Time Series DBMS

Time Series DBMS
Vector DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Website

github.com/spotify/heroic

kx.com

tempoiq.com (offline)

github.com/thinkaurelius/titan

Technical documentation

spotify.github.io/heroic

code.kx.com

github.com/thinkaurelius/titan/wiki

Developer

Spotify

Kx Systems, a division of First Derivatives plc

TempoIQ

Aurelius, owned by DataStax

Initial release

2014

2000

kdb was released 2000, kdb+ in 2003

2012

Current release

3.6, May 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free 32-bit version

commercial

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

yes

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
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

APIs and other access methods

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

with views

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

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.

yes

User concepts

Access control

rights management via user accounts

simple authentication-based access control

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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

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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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