DBMS > Cloudflare Workers KV vs. jBASE vs. RRDtool vs. WakandaDB

System Properties Comparison Cloudflare Workers KV vs. jBASE vs. RRDtool vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

A robust multi-value DBMS comprising development tools and middleware

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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

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

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

oss.oetiker.ch/rrdtool

wakanda.github.io

Technical documentation

developers.cloudflare.com/kv/api

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

oss.oetiker.ch/rrdtool/doc

wakanda.github.io/doc

Developer

Cloudflare

Rocket Software (formerly Zumasys)

Tobias Oetiker

Wakanda SAS

Initial release

2018

1991

1999

2012

Current release

5.7

1.8.0, 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

Open Source

AGPLv3, extended commercial license available

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

Implementations in Java (e.g. RRD4J) and C# available

C++, JavaScript

Server operating systems

hosted

AIX
Linux
Windows

HP-UX
Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

optional

Numeric data only

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.

yes

Exporting into and restoring from XML files possible

Secondary indexes

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

APIs and other access methods

HTTP REST
Proprietary protocol

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

in-process shared library
Pipes

RESTful HTTP API

Supported programming languages

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
Basic
Jabbascript
Java

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

User concepts

Access control

Access rights can be defined down to the item level

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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