DBMS > Apache IoTDB vs. Hazelcast vs. Percona Server for MySQL

System Properties Comparison Apache IoTDB vs. Hazelcast vs. Percona Server for MySQL

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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 widely adopted in-memory data grid

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

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

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Website

iotdb.apache.org

hazelcast.com

www.percona.com/software/mysql-database/percona-server

Technical documentation

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

hazelcast.org/imdg/docs

www.percona.com/downloads/Percona-Server-LATEST

Developer

Apache Software Foundation

Hazelcast

Percona

Initial release

2018

2008

Current release

1.1.0, April 2023

5.3.6, November 2023

8.0.36-28, 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2

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)

All OS with a Java VM

Linux

Data scheme

yes

schema-free

yes

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.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

yes

Replicated Map

Multi-source replication
Source-replica replication
XtraDB Cluster

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

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

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

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