DBMS > DataFS vs. Elasticsearch vs. openGemini

System Properties Comparison DataFS vs. Elasticsearch vs. openGemini

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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.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Primary database model

Object oriented DBMS

Search engine
Vector DBMS

Time Series DBMS

Secondary database models

Graph DBMS

Document store
Spatial DBMS

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

Score	0.01
Rank	#376	Overall
	#18	Object oriented DBMS

Score	131.85
Rank	#8	Overall
	#1	Search engines
	#1	Vector DBMS

Score	0.00
Rank	#388	Overall
	#40	Time Series DBMS

Website

newdatabase.com

www.elastic.co/elasticsearch

www.opengemini.org
github.com/openGemini

Technical documentation

dev.mobiland.com/Overview.xsp

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

docs.opengemini.org/guide

Developer

Mobiland AG

Elastic

Huawei and openGemini community

Initial release

2018

2010

2022

Current release

1.1.263, October 2022

8.6, January 2023

1.1, July 2023

License

Commercial or Open Source

commercial

Open Source

Elastic License

Open Source

Apache Version 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

Java

Server operating systems

Windows

All OS with a Java VM

Linux
Windows

Data scheme

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

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Java API
RESTful HTTP/JSON API

HTTP REST

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Triggers

no, except callback-events from server when changes happened

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

Windows-Profile

Administrators and common users accounts

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2017
2 January 2018, Paul Andlinger, Matthias Gelbmann

Elasticsearch moved into the top 10 most popular database management systems
3 July 2017, Matthias Gelbmann

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

show all

Recent citations in the news

Elastic founder on returning to open source four years after going proprietary
29 September 2024, TechCrunch

Elasticsearch will be open source again as CTO declares changed landscape
2 September 2024, DevClass

Elasticsearch Open Inference API and Playground Support Google Cloud’s Vertex AI Platform
27 September 2024, Business Wire

Elasticsearch Open Inference API now Supports Google AI Studio
27 September 2024, StockTitan

Elastic returns to open source, but can it regain the community’s trust? Some industry players aren’t holding their breath
6 September 2024, ITPro

provided by Google News

Open Source @ Huawei
9 February 2022, huawei.com

provided by Google News

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