DBMS > EsgynDB vs. OpenMLDB vs. ReductStore

System Properties Comparison EsgynDB vs. OpenMLDB vs. ReductStore

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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

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.

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.15
Rank	#332	Overall
	#144	Relational DBMS

Score	0.05
Rank	#358	Overall
	#38	Time Series DBMS

Score	0.06
Rank	#355	Overall
	#37	Time Series DBMS

Website

www.esgyn.cn

openmldb.ai

github.com/reductstore
www.reduct.store

Technical documentation

openmldb.ai/docs/zh/main

www.reduct.store/docs

Developer

Esgyn

4 Paradigm Inc.

ReductStore LLC

Initial release

2015

2020

2023

Current release

2024-2 February 2024

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

C++, Java, Scala

C++, Rust

Server operating systems

Linux

Docker
Linux
macOS
Windows

Data scheme

yes

Fixed schema

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

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C++
Go
Java
Python
Scala

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

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

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