DBMS > Hazelcast vs. IRONdb vs. SiteWhere vs. SwayDB

System Properties Comparison Hazelcast vs. IRONdb vs. SiteWhere vs. SwayDB

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Editorial information provided by DB-Engines

Name

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

Description

A widely adopted in-memory data grid

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

M2M integration platform for persisting/querying time series data

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Key-value store

Time Series DBMS

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

hazelcast.com

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

github.com/sitewhere/sitewhere

swaydb.simer.au

Technical documentation

hazelcast.org/imdg/docs

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

sitewhere1.sitewhere.io/index.html

Developer

Hazelcast

Circonus LLC.

SiteWhere

Simer Plaha

Initial release

2008

2017

2010

2018

Current release

5.3.6, November 2023

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

GNU Affero GPL V3.0

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++

Java

Scala

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

schema-free

predefined scheme

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

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

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

HTTP API

HTTP REST

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes, in Lua

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

configurable replication factor, datacenter aware

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

Atomic execution of operations

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

Role-based access control

Users with fine-grained authorization concept

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