DBMS > Blazegraph vs. Cubrid vs. Faircom EDGE vs. Vitess

System Properties Comparison Blazegraph vs. Cubrid vs. Faircom EDGE vs. Vitess

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

blazegraph.com

cubrid.com (korean)
cubrid.org (english)

www.faircom.com/products/faircom-edge

vitess.io

Technical documentation

wiki.blazegraph.com

cubrid.org/manuals

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

vitess.io/docs

Developer

Blazegraph

CUBRID Corporation, CUBRID Foundation

FairCom Corporation

The Linux Foundation, PlanetScale

Initial release

2006

2008

1979

2013

Current release

2.1.5, March 2019

11.0, January 2021

V3, October 2020

15.0.2, December 2022

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

Apache Version 2.0, commercial licenses available

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

Java

C, C++, Java

ANSI C, C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

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

SQL

Support of SQL

SPARQL is used as query language

yes

ANSI SQL queries

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
JDBC
ODBC
OLE DB

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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

.Net, JavaScript, C/C++

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

when using SQL

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

table locks or row locks depending on storage engine

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

fine grained access rights according to SQL-standard

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

Users with fine-grained authorization concept

no user groups or roles

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