DBMS > OpenMLDB vs. Quasardb vs. TerminusDB vs. VelocityDB

System Properties Comparison OpenMLDB vs. Quasardb vs. TerminusDB vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

An open-source machine learning database that provides a feature platform for training and inference

Distributed, high-performance timeseries database

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Time Series DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Relational DBMS

Document store
RDF store

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

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

Technical documentation

openmldb.ai/docs/zh/main

doc.quasar.ai/master

terminusdb.github.io/terminusdb/#

velocitydb.com/UserGuide

Developer

4 Paradigm Inc.

quasardb

DataChemist Ltd.

VelocityDB Inc

Initial release

2020

2009

2018

2011

Current release

2024-2 February 2024

3.14.1, January 2024

11.0.0, January 2023

7.x

License

Commercial or Open Source

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPL V3

commercial

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, Scala

C++

Prolog, Rust

Server operating systems

Linux

BSD
Linux
OS X
Windows

Linux

Any that supports .NET

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

JDBC
SQLAlchemy

HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

.Net

Supported programming languages

C++
Go
Java
Python
Scala

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript
Python

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

consistent hashing

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication with selectable replication factor

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

by using LevelDB

yes

in-memory journaling

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

Role-based access control

Based on Windows Authentication

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