DBMS > EsgynDB vs. Hypertable vs. RDF4J vs. YTsaurus

System Properties Comparison EsgynDB vs. Hypertable vs. RDF4J vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An open source BigTable implementation based on distributed file systems such as Hadoop

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

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Relational DBMS

Wide column store

RDF store

Document store
Key-value store

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

www.esgyn.cn

rdf4j.org

ytsaurus.tech

Technical documentation

rdf4j.org/documentation

ytsaurus.tech/docs/en

Developer

Esgyn

Hypertable Inc.

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

Yandex

Initial release

2015

2009

2004

2023

Current release

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

GNU version 3. Commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache License, Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

C++

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Unix
Windows

Ubuntu

Data scheme

yes

schema-free

yes

RDF Schemas

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.

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

YQL, an SQL-based language, is supported

APIs and other access methods

ADO.NET
JDBC
ODBC

C++ API
Thrift

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++
Java
Perl
PHP
Python
Ruby

Java
PHP
Python

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor on file system level

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists

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