DBMS > EsgynDB vs. HyperSQL vs. SvectorDB

System Properties Comparison EsgynDB vs. HyperSQL vs. SvectorDB

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Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Serverless cloud-native vector database

Primary database model

Relational DBMS

Vector DBMS

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

Score	0.16
Rank	#324	Overall
	#145	Relational DBMS

Score	2.95
Rank	#90	Overall
	#48	Relational DBMS

Score	0.00
Rank	#392	Overall
	#19	Vector DBMS

Website

www.esgyn.cn

hsqldb.org

svectordb.com

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

www.svectordb.com/docs

Developer

Esgyn

SvectorDB

Initial release

2015

2001

2023

Current release

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Java

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

server-less

Data scheme

yes

Typing

predefined data types such as float or date

yes

string, double, vector

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

HTTP API

JDBC via HTTP
JDBC
ODBC

OpenAPI 3.0, RESTful HTTP API, Python SDK, JavaScript / TypeScript SDK

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

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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