DBMS > Bangdb vs. Fauna vs. KeyDB vs. Tkrzw

System Properties Comparison Bangdb vs. Fauna vs. KeyDB vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	1.55
Rank	#143	Overall
	#26	Document stores
	#13	Graph DBMS
	#66	Relational DBMS
	#13	Time Series DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

bangdb.com

fauna.com

github.com/Snapchat/KeyDB
keydb.dev

dbmx.net/tkrzw

Technical documentation

docs.bangdb.com

docs.fauna.com

docs.keydb.dev

Developer

Sachin Sinha, BangDB

Fauna, Inc.

EQ Alpha Technology Ltd.

Mikio Hirabayashi

Initial release

2012

2014

2019

2020

Current release

BangDB 2.0, October 2021

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

BSD-3

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Scala

C++

Server operating systems

Linux

hosted

Linux

Linux
macOS

Data scheme

schema-free

Typing

predefined data types such as float or date

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

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

C
C#
C++
Java
Python

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Lua

Triggers

yes, Notifications (with Streaming only)

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

horizontal partitioning

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

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

Configurable mechanisms for persistency via snapshots and/or operations logs

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

yes

using specific database classes

User concepts

Access control

yes (enterprise version only)

Identity management, authentication, and access control

simple password-based access control and ACL

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