DBMS > Apache IoTDB vs. Graphite vs. Tkrzw vs. Yanza

System Properties Comparison Apache IoTDB vs. Graphite vs. Tkrzw vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Time Series DBMS for IoT Applications

Primary database model

Time Series DBMS

Key-value store

Time Series DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

iotdb.apache.org

github.com/graphite-project/graphite-web

dbmx.net/tkrzw

yanza.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

graphite.readthedocs.io

Developer

Apache Software Foundation

Chris Davis

Mikio Hirabayashi

Yanza

Initial release

2018

2006

2020

2015

Current release

1.1.0, April 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

Python

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Unix

Linux
macOS

Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JDBC
Native API

HTTP API
Sockets

HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

JavaScript (Node.js)
Python

C++
Java
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrency

Support for concurrent manipulation of data

yes

locking

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.

yes

using specific database classes

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

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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