DBMS > EsgynDB vs. OpenMLDB vs. OpenTenBase

System Properties Comparison EsgynDB vs. OpenMLDB vs. OpenTenBase

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Editorial information provided by DB-Engines

Name

Description

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

An enterprise-level distributed HTAP open source database based on PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

www.esgyn.cn

openmldb.ai

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

openmldb.ai/docs/zh/main

docs.opentenbase.org
docs.opentenbase.org/en

Developer

Esgyn

4 Paradigm Inc.

OpenAtom Foundation, previously Tencent

Initial release

2015

2020

Current release

2024-2 February 2024

2.5, January 2024

License

Commercial or Open Source

commercial

Open Source

BSD-3

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++, Java, Scala

Server operating systems

Linux

Data scheme

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

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
SQLAlchemy

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Go
Java
Python
Scala

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

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

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.

yes

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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