DBMS > Faircom EDGE vs. GBase vs. Riak KV vs. StarRocks

System Properties Comparison Faircom EDGE vs. GBase vs. Riak KV vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Distributed, fault tolerant key-value store

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

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

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

www.faircom.com/products/faircom-edge

www.gbase.cn

www.starrocks.io

Technical documentation

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

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

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

FairCom Corporation

General Data Technology Co., Ltd.

OpenSource, formerly Basho Technologies

The Linux Foundation

since Feb 2023

Initial release

1979

2004

2009

2020

Current release

V3, October 2020

GBase 8a, GBase 8s, GBase 8c

3.2.0, December 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

C, Java, Python

Erlang

C++, Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux

Linux
OS X

Linux

Data scheme

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

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

ANSI SQL queries

Standard with numerous extensions

yes

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

HTTP API
Native Erlang Interface

JDBC
MySQL protocol

Supported programming languages

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

Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

no "single point of failure"

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

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

across SQL and NoSQL

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

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

yes

yes, using Riak Security

Role based access control and fine grained access rights

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