DBMS > AlaSQL vs. Elasticsearch vs. openGemini

System Properties Comparison AlaSQL vs. Elasticsearch vs. openGemini

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Document store
Relational DBMS

Search engine
Vector DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.39
Rank	#260	Overall
	#42	Document stores
	#120	Relational DBMS

Score	131.38
Rank	#8	Overall
	#1	Search engines
	#1	Vector DBMS

Score	0.04
Rank	#366	Overall
	#39	Time Series DBMS

Website

alasql.org

www.elastic.co/elasticsearch

www.opengemini.org
github.com/openGemini

Technical documentation

github.com/AlaSQL/alasql

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

docs.opengemini.org/guide

Developer

Andrey Gershun & Mathias R. Wulff

Elastic

Huawei and openGemini community

Initial release

2014

2010

2022

Current release

8.6, January 2023

1.1, July 2023

License

Commercial or Open Source

Open Source

MIT-License

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

JavaScript

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

All OS with a Java VM

Linux
Windows

Data scheme

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like query language

APIs and other access methods

JavaScript API

Java API
RESTful HTTP/JSON API

HTTP REST

Supported programming languages

JavaScript

.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

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

yes

only for local storage and DOM-storage

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

In-memory capabilities

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

yes

Memcached and Redis integration

yes

User concepts

Access control

Administrators and common users accounts

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More resources

DB-Engines blog posts

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2 January 2018, Paul Andlinger, Matthias Gelbmann

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2 March 2016, Paul Andlinger

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