DBMS > Alibaba Cloud Table Store vs. GraphDB vs. Infobright vs. MySQL

System Properties Comparison Alibaba Cloud Table Store vs. GraphDB vs. Infobright vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Widely used open source RDBMS

Primary database model

Wide column store

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.24
Rank	#310	Overall
	#12	Wide column stores

Score	3.10
Rank	#100	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	1.00
Rank	#193	Overall
	#90	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.ontotext.com

ignitetech.com/softwarelibrary/infobrightdb

www.mysql.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

graphdb.ontotext.com/documentation

dev.mysql.com/doc

Social network pages

Developer

Alibaba

Ontotext

Ignite Technologies Inc.; formerly InfoBright Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2000

2005

1995

Current release

10.4, October 2023

8.3.0, January 2024

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

hosted

All OS with a Java VM
Linux
OS X
Windows

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

yes

Typing

predefined data types such as float or date

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, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

with proprietary extensions

APIs and other access methods

HTTP API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Python

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

well-defined plugin interfaces; JavaScript server-side extensibility

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

Source-replica replication

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

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-row operations

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

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

Access rights based on subaccounts and tokens

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

How Knowledge Graphs Power Data Mesh and Data Fabric
10 April 2024

Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI
3 April 2024

Using GraphDB’s Natural Language Interface to Talk with Your Content
29 March 2024

Choosing A Graph Data Model to Best Serve Your Use Case
27 March 2024

Event Extraction Based on Fine-Tuned Text2Event Transformer Speeds up the Fact-checking Process
22 March 2024

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