DBMS > Heroic vs. Riak TS vs. Titan vs. WakandaDB vs. Yanza

System Properties Comparison Heroic vs. Riak TS vs. Titan vs. WakandaDB vs. Yanza

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.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Titan is a Graph DBMS optimized for distributed clusters.

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Time Series DBMS for IoT Applications

Primary database model

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

github.com/spotify/heroic

github.com/thinkaurelius/titan

wakanda.github.io

yanza.com

Technical documentation

spotify.github.io/heroic

www.tiot.jp/riak-docs/riak/ts/latest

github.com/thinkaurelius/titan/wiki

wakanda.github.io/doc

Developer

Spotify

Open Source, formerly Basho Technologies

Aurelius, owned by DataStax

Wakanda SAS

Yanza

Initial release

2014

2015

2012

2015

Current release

3.0.0, September 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache license, version 2.0

Open Source

AGPLv3, extended commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

Java

C++, JavaScript

Server operating systems

Linux
OS X

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes, limited

APIs and other access methods

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

HTTP API
Native Erlang Interface

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

HTTP API

Supported programming languages

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Clojure
Java
Python

JavaScript

any language that supports HTTP calls

Server-side scripts

Stored procedures

Erlang

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

via pluggable storage backends

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

none

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

Eventual Consistency
Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

User authentification and security via Rexster Graph Server

yes

More information provided by the system vendor

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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

show all

Recent citations in the news

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

New Basho Data Platform Provides Operational Simplicity for Enterprise Big Data Applications
7 June 2015, insideBIGDATA

provided by Google News

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

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

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

Database Deep Dives: JanusGraph
8 August 2019, IBM

provided by Google News

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