DBMS > Apache IoTDB vs. IBM Cloudant vs. JaguarDB vs. OpenMLDB vs. SQLite

System Properties Comparison Apache IoTDB vs. IBM Cloudant vs. JaguarDB vs. OpenMLDB vs. SQLite

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

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

An open-source machine learning database that provides a feature platform for training and inference

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Document store

Key-value store
Vector DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

iotdb.apache.org

www.ibm.com/products/cloudant

www.jaguardb.com

openmldb.ai

www.sqlite.org

Technical documentation

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

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

openmldb.ai/docs/zh/main

www.sqlite.org/docs.html

Developer

Apache Software Foundation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

4 Paradigm Inc.

Dwayne Richard Hipp

Initial release

2018

2010

2015

2020

2000

Current release

1.1.0, April 2023

3.3 July 2023

2024-2 February 2024

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3.0

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

C++

the server part. Clients available in other languages

C++, Java, Scala

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

Linux

server-less

Data scheme

yes

schema-free

yes

Fixed schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
Native API

RESTful HTTP/JSON API

JDBC
ODBC

JDBC
SQLAlchemy

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Go
Java
Python
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning

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

Multi-source replication
Source-replica replication

Multi-source replication

Source-replica replication

none

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

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

via file-system locks

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

Access rights for users can be defined per database

rights management via user accounts

fine grained access rights according to SQL-standard

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