DBMS > Elasticsearch vs. EsgynDB vs. OpenMLDB vs. Sadas Engine

System Properties Comparison Elasticsearch vs. EsgynDB vs. OpenMLDB vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

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

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

An open-source machine learning database that provides a feature platform for training and inference

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Relational DBMS

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

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

www.elastic.co/elasticsearch

www.esgyn.cn

openmldb.ai

www.sadasengine.com

Technical documentation

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

openmldb.ai/docs/zh/main

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Elastic

Esgyn

4 Paradigm Inc.

SADAS s.r.l.

Initial release

2010

2015

2020

2006

Current release

8.6, January 2023

2024-2 February 2024

8.0

License

Commercial or Open Source

Open Source

Elastic License

commercial

Open Source

commercial

free trial version available

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

C++, Java

C++, Java, Scala

C++

Server operating systems

All OS with a Java VM

Linux

AIX
Linux
Windows

Data scheme

schema-free

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

yes

Fixed schema

yes

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JDBC
SQLAlchemy

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C++
Go
Java
Python
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Immediate Consistency

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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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

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22 May 2024, Business Wire

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12 January 2024, SentinelOne

Netflix Uses Elasticsearch Percolate Queries to Implement Reverse Searches Efficiently
29 April 2024, InfoQ.com

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21 May 2024, Business Wire

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23 August 2021, Towards Data Science

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13 August 2021, Towards Data Science

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3 August 2021, Towards Data Science

provided by Google News

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