DBMS > HugeGraph vs. HyperSQL vs. Valentina Server vs. YDB

System Properties Comparison HugeGraph vs. HyperSQL vs. Valentina Server vs. YDB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Object-relational database and reports server

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Graph DBMS

Relational DBMS

Document store
Relational DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

hsqldb.org

www.valentina-db.net

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

hugegraph.apache.org/docs

hsqldb.org/web/hsqlDocsFrame.html

valentina-db.com/docs/dokuwiki/v5/doku.php

ydb.tech/en/docs

Developer

Baidu

Paradigma Software

Yandex

Initial release

2018

2001

1999

2019

Current release

0.9

2.7.2, June 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

based on BSD license

commercial

Open Source

Apache 2.0; commercial license 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

Server operating systems

Linux
macOS
Unix

All OS with a Java VM

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

Linux
OS X
Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like query language (YQL)

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

JDBC via HTTP
JDBC
ODBC

ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Groovy
Java
Python

All languages supporting JDBC/ODBC
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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More resources

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