DBMS > Apache IoTDB vs. openGemini vs. Percona Server for MongoDB

System Properties Comparison Apache IoTDB vs. openGemini vs. Percona Server for MongoDB

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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

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Time Series DBMS

Document store

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Website

iotdb.apache.org

www.opengemini.org
github.com/openGemini

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

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

docs.opengemini.org/guide

docs.percona.com/percona-distribution-for-mongodb

Developer

Apache Software Foundation

Huawei and openGemini community

Percona

Initial release

2018

2022

2015

Current release

1.1.0, April 2023

1.1, July 2023

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

APIs and other access methods

JDBC
Native API

HTTP REST

proprietary protocol using JSON

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

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

Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

via In-Memory Engine

User concepts

Access control

yes

Administrators and common users accounts

Access rights for users and roles

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