DBMS > Bangdb vs. Faircom EDGE vs. Riak KV vs. STSdb

System Properties Comparison Bangdb vs. Faircom EDGE vs. Riak KV vs. STSdb

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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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Distributed, fault tolerant key-value store

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store
Relational DBMS

Key-value store

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

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

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

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

bangdb.com

www.faircom.com/products/faircom-edge

github.com/STSSoft/STSdb4

Technical documentation

docs.bangdb.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

Developer

Sachin Sinha, BangDB

FairCom Corporation

OpenSource, formerly Basho Technologies

STS Soft SC

Initial release

2012

1979

2009

2011

Current release

BangDB 2.0, October 2021

V3, October 2020

3.2.0, December 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSD 3

commercial

Restricted, free version available

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

ANSI C, C++

Erlang

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux
OS X

Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

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

yes, ANSI Standard SQL Types

yes

primitive types and user defined types (classes)

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

restricted

SQL

Support of SQL

SQL like support with command line tool

yes

ANSI SQL queries

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

.NET Client API

Supported programming languages

C
C#
C++
Java
Python

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

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

C#
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Erlang

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

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

File partitioning

Customizable business rules for partitioning

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Synchronous and asynchronous realtime replication based on transaction logs

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

links between data sets can be stored

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

across SQL and NoSQL

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

yes

User concepts

Access control

yes (enterprise version only)

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

yes, using Riak Security

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