DBMS > EsgynDB vs. HBase vs. Microsoft Azure AI Search vs. RDF4J

System Properties Comparison EsgynDB vs. HBase vs. Microsoft Azure AI Search vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Wide-column store based on Apache Hadoop and on concepts of BigTable

Search-as-a-service for web and mobile app development

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Secondary database models

Vector DBMS

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

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

www.esgyn.cn

hbase.apache.org

azure.microsoft.com/en-us/services/search

rdf4j.org

Technical documentation

hbase.apache.org/book.html

learn.microsoft.com/en-us/azure/search

rdf4j.org/documentation

Developer

Esgyn

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2015

2008

2015

2004

Current release

2.3.4, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

Java

Server operating systems

Linux

Linux
Unix
Windows

using Cygwin

hosted

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free, schema definition possible

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
Java
JavaScript
Python

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Coprocessors in Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes

using Azure authentication

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