DBMS > Apache IoTDB vs. IRONdb vs. Realm vs. STSdb vs. Yaacomo

System Properties Comparison Apache IoTDB vs. IRONdb vs. Realm vs. STSdb vs. Yaacomo

Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is removed 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 distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

iotdb.apache.org

www.circonus.com/solutions/time-series-database/

realm.io

github.com/STSSoft/STSdb4

yaacomo.com

Technical documentation

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

docs.circonus.com/irondb/category/getting-started

realm.io/docs

Developer

Apache Software Foundation

Circonus LLC.

Realm, acquired by MongoDB in May 2019

STS Soft SC

Q2WEB GmbH

Initial release

2018

2017

2014

2011

2009

Current release

1.1.0, April 2023

V0.10.20, January 2018

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Android
Backend: server-less
iOS
Windows

Windows

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

SQL-like query language

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
Native API

HTTP API

.NET Client API

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
Java

Server-side scripts

Stored procedures

yes

yes, in Lua

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

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

Automatic, metric affinity per node

none

horizontal partitioning

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

configurable replication factor, datacenter aware

none

Source-replica replication

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 per node, eventual consistency across nodes

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

In-Memory realm

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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