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

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

Editorial information provided by DB-Engines

Name

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

Scalable Time Series DBMS based on HBase

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

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

Time Series DBMS

Object oriented DBMS

Time Series DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1.68
Rank	#142	Overall
	#12	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

opentsdb.net

wakanda.github.io

yanza.com

Technical documentation

spotify.github.io/heroic

opentsdb.net/docs/build/html/index.html

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

wakanda.github.io/doc

Developer

Spotify

currently maintained by Yahoo and other contributors

Open Source, formerly Basho Technologies

Wakanda SAS

Yanza

Initial release

2014

2011

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

LGPL

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

C++, JavaScript

Server operating systems

Linux
Windows

Linux
OS X

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

SQL

Support of SQL

yes, limited

APIs and other access methods

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

HTTP API
Telnet API

HTTP API
Native Erlang Interface

RESTful HTTP API

HTTP API

Supported programming languages

Erlang
Go
Java
Python
R
Ruby

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

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

based on HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

In-memory capabilities

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

User concepts

Access control

yes

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

show all

Recent citations in the news

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

provided by Google News

Pinterest Switches from OpenTSDB to Their Own Time Series Database
16 September 2018, InfoQ.com

Brain Monitoring with Kafka, OpenTSDB, and Grafana
5 August 2016, KDnuggets

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

LogicMonitor Rolls a Time Series Database for Finer-Grain Reporting
1 June 2016, The New Stack

provided by Google News

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