DBMS > Apache IoTDB vs. FileMaker vs. OpenTSDB vs. Snowflake

System Properties Comparison Apache IoTDB vs. FileMaker vs. OpenTSDB vs. Snowflake

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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

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

Scalable Time Series DBMS based on HBase

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

iotdb.apache.org

www.claris.com/filemaker

opentsdb.net

www.snowflake.com

Technical documentation

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

www.claris.com/resources/documentation

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

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Claris

a subsidiary of Apple

currently maintained by Yahoo and other contributors

Snowflake Computing Inc.

Initial release

2018

1983

2011

2014

Current release

1.1.0, April 2023

19.4.1, November 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

LGPL

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java VM (>= 1.8)

iOS

client part only
Linux
OS X
Windows

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

A http query request can return the data in XML format

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

via plugins

yes

APIs and other access methods

JDBC
Native API

Filemaker WebDirect
JDBC
ODBC

HTTP API
Telnet API

CLI Client
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

PHP

Erlang
Go
Java
Python
R
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

based on HBase

yes

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

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on HBase

yes

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

Immediate Consistency

based on HBase

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

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

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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