DBMS > Apache IoTDB vs. MaxDB vs. Percona Server for MongoDB vs. PlanetScale vs. TimesTen

System Properties Comparison Apache IoTDB vs. MaxDB vs. Percona Server for MongoDB vs. PlanetScale vs. TimesTen

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 robust and reliable RDBMS optimized to run all major SAP solutions

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

Scalable, distributed, serverless MySQL database platform built on top of Vitess

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	2.65
Rank	#111	Overall
	#55	Relational DBMS

Score	0.55
Rank	#253	Overall
	#39	Document stores

Score	1.75
Rank	#146	Overall
	#67	Relational DBMS

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

iotdb.apache.org

maxdb.sap.com

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

planetscale.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

maxdb.sap.com/documentation

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

planetscale.com/docs

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

SAP, acquired from Software AG (Adabas-D) in 1997

Percona

PlanetScale

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

1984

2015

2020

1998

Current release

1.1.0, April 2023

7.9.10.12, February 2024

3.4.10-2.10, November 2017

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Limited community edition free

Open Source

GPL Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

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)

AIX
HP-UX
Linux
Solaris
Windows

Linux

Docker
Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC
WebDAV

proprietary protocol using JSON

ADO.NET
JDBC
MySQL protocol
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C#
Java
Perl
PHP
Python

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

JavaScript

yes

proprietary syntax

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

none

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

Multi-source replication
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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

via In-Memory Engine

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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