DBMS > Apache IoTDB vs. Cloudflare Workers KV vs. eXtremeDB

System Properties Comparison Apache IoTDB vs. Cloudflare Workers KV vs. eXtremeDB

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Primary database model

Time Series DBMS

Key-value store

Relational DBMS
Time Series DBMS

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

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.29
Rank	#283	Overall
	#40	Key-value stores

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Website

iotdb.apache.org

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

www.mcobject.com

Technical documentation

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

developers.cloudflare.com/kv/api

www.mcobject.com/docs/extremedb.htm

Developer

Apache Software Foundation

Cloudflare

McObject

Initial release

2018

2001

Current release

1.1.0, April 2023

8.2, 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

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 and C++

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

AIX
HP-UX
Linux
macOS
Solaris
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.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with the option: eXtremeSQL

APIs and other access methods

JDBC
Native API

HTTP REST
Proprietary protocol

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C
C#
C++
Java
Lua
Python
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning / 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

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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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