DBMS > Apache IoTDB vs. ClickHouse vs. FileMaker vs. Graphite vs. Trafodion

System Properties Comparison Apache IoTDB vs. ClickHouse vs. FileMaker vs. Graphite vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. 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

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.

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Transactional SQL-on-Hadoop DBMS

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	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Website

iotdb.apache.org

clickhouse.com

www.claris.com/filemaker

github.com/graphite-project/graphite-web

trafodion.apache.org

Technical documentation

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

clickhouse.com/docs

www.claris.com/resources/documentation

graphite.readthedocs.io

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Clickhouse Inc.

Claris

a subsidiary of Apple

Chris Davis

Apache Software Foundation, originally developed by HP

Initial release

2018

2016

1983

2006

2014

Current release

1.1.0, April 2023

v24.4.1.2088-stable, May 2024

19.4.1, November 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Python

C++, Java

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
macOS

iOS

client part only
Linux
OS X
Windows

Linux
Unix

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Close to ANSI SQL (SQL/JSON + extensions)

yes

via plugins

yes

APIs and other access methods

JDBC
Native API

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

Filemaker WebDirect
JDBC
ODBC

HTTP API
Sockets

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

PHP

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

key based and custom

none

Sharding

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

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

Source-replica replication, warm standby

since Version 14

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

yes

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.

simple rights management via user accounts and connection to external directory services

fine grained access rights according to SQL-standard

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