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DBMS > Faircom DB vs. KeyDB vs. Riak KV vs. SQL.JS

System Properties Comparison Faircom DB vs. KeyDB vs. Riak KV vs. SQL.JS

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Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

Distributed, fault tolerant key-value store

Port of SQLite to JavaScript

Primary database model

Key-value store
Relational DBMS

Key-value store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

www.faircom.com/products/faircom-db

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.tiot.jp/riak-docs/riak/kv/latest

sql.js.org/documentation/index.html

Developer

FairCom Corporation

EQ Alpha Technology Ltd.

OpenSource, formerly Basho Technologies

Alon Zakai

enhancements implemented by others

Initial release

1979

2019

2009

2012

Current release

V12, November 2020

3.2.0, December 2022

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

BSD-3

Open Source

Apache version 2, commercial enterprise edition

Open Source

Cloud-based only

Only available as a cloud service

no

no

no

no

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

ANSI C, C++

C++

Erlang

JavaScript

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema free, schema optional, schema required, partial schema,

schema-free

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

partial

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

no

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.

no

no

no

no

Secondary indexes

yes

yes

by using the Redis Search module

restricted

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

no

no

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Proprietary protocol

RESP - REdis Serialization Protoco

HTTP API
Native Erlang Interface

JavaScript API

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Lua

Erlang

no

Triggers

yes

no

yes

pre-commit hooks and post-commit hooks

no

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Multi-source replication
Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

no

no

yes

no

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Strong eventual consistency with CRDTs

Eventual Consistency

none

Foreign keys

Referential integrity

yes

no

no

links between data sets can be stored

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

Optimistic locking, atomic execution of commands blocks and scripts

no

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

no

except by serializing a db to a file

In-memory capabilities

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

yes

yes

yes

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

simple password-based access control and ACL

yes, using Riak Security

no

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