DBMS > DataFS vs. EsgynDB vs. ReductStore vs. TinkerGraph

System Properties Comparison DataFS vs. EsgynDB vs. ReductStore vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Secondary database models

Graph DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.08
Rank	#345	Overall
	#34	Graph DBMS

Website

newdatabase.com

www.esgyn.cn

github.com/reductstore
www.reduct.store

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

dev.mobiland.com/Overview.xsp

www.reduct.store/docs

Developer

Mobiland AG

Esgyn

ReductStore LLC

Initial release

2018

2015

2023

2009

Current release

1.1.263, October 2022

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

Open Source

Apache 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

C++, Java

C++, Rust

Java

Server operating systems

Windows

Linux

Docker
Linux
macOS
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

schema-free

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

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

HTTP API

TinkerPop 3

Supported programming languages

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

C++
JavaScript (Node.js)
Python
Rust

Groovy
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

Windows-Profile

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune
3 June 2024, AWS Blog

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

provided by Google News

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