DBMS > Apache IoTDB vs. Cloudflare Workers KV vs. FoundationDB vs. mSQL vs. SQLite

System Properties Comparison Apache IoTDB vs. Cloudflare Workers KV vs. FoundationDB vs. mSQL vs. SQLite

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

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 global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Ordered key-value store. Core features are complimented by layers.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

iotdb.apache.org

www.cloudflare.com/developer-platform/workers-kv

github.com/apple/foundationdb

hughestech.com.au/products/msql

www.sqlite.org

Technical documentation

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

developers.cloudflare.com/kv/api

apple.github.io/foundationdb

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Cloudflare

FoundationDB

Hughes Technologies

Dwayne Richard Hipp

Initial release

2018

2013

1994

2000

Current release

1.1.0, April 2023

6.2.28, November 2020

4.4, October 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

Public Domain

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)

hosted

Linux
OS X
Windows

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

server-less

Data scheme

yes

schema-free

some layers support schemas

yes

dynamic column types

Typing

predefined data types such as float or date

yes

some layers support typing

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

supported in specific SQL layer only

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
Native API

HTTP REST
Proprietary protocol

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C++
Delphi
Java
Perl
PHP
Tcl

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

in SQL-layer only

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Linearizable consistency

none

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

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