DBMS > Bangdb vs. Cloudflare Workers KV vs. DataFS vs. Trafodion

System Properties Comparison Bangdb vs. Cloudflare Workers KV vs. DataFS vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Object oriented DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Graph DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Website

bangdb.com

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

newdatabase.com

trafodion.apache.org

Technical documentation

docs.bangdb.com

developers.cloudflare.com/kv/api

dev.mobiland.com/Overview.xsp

trafodion.apache.org/documentation.html

Developer

Sachin Sinha, BangDB

Cloudflare

Mobiland AG

Apache Software Foundation, originally developed by HP

Initial release

2012

2018

2014

Current release

BangDB 2.0, October 2021

1.1.263, October 2022

2.3.0, February 2019

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

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

C, C++

C++, Java

Server operating systems

Linux

hosted

Windows

Linux

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP REST
Proprietary protocol

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes, Notifications (with Streaming only)

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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 concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Windows-Profile

fine grained access rights according to SQL-standard

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