DBMS > EsgynDB vs. Machbase Neo vs. NSDb

System Properties Comparison EsgynDB vs. Machbase Neo vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

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

TimeSeries DBMS for AIoT and BigData

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Relational DBMS

Time Series DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

www.esgyn.cn

machbase.com

nsdb.io

Technical documentation

machbase.com/dbms

nsdb.io/Architecture

Developer

Esgyn

Machbase

Initial release

2015

2013

2017

Current release

V8.0, August 2023

License

Commercial or Open Source

commercial

free test version available

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

C++, Java

Java, Scala

Server operating systems

Linux

Linux
macOS
Windows

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, 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 fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

Using Apache Lucene

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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