DBMS > Apache IoTDB vs. Apache Jena - TDB vs. ClickHouse vs. PouchDB

System Properties Comparison Apache IoTDB vs. Apache Jena - TDB vs. ClickHouse vs. PouchDB

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Editorial information provided by DB-Engines

Name

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

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Secondary database models

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	3.75
Rank	#84	Overall
	#3	RDF stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

iotdb.apache.org

jena.apache.org/documentation/tdb/index.html

clickhouse.com

pouchdb.com

Technical documentation

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

jena.apache.org/documentation/tdb/index.html

clickhouse.com/docs

pouchdb.com/guides

Developer

Apache Software Foundation

originally developed by HP Labs

Clickhouse Inc.

Apache Software Foundation

Initial release

2018

2000

2016

2012

Current release

1.1.0, April 2023

4.9.0, July 2023

v24.4.1.2088-stable, May 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License, Version 2.0

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

FreeBSD
Linux
macOS

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

RDF Schemas

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 views

SQL

Support of SQL

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

JDBC
Native API

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

JavaScript

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

key based and custom

Sharding

with a proxy-based framework, named couchdb-lounge

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

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

TDB Transactions

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

yes

Access control via Jena Security

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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