DBMS > EsgynDB vs. OpenQM vs. Qdrant vs. Spark SQL vs. Trafodion

System Properties Comparison EsgynDB vs. OpenQM vs. Qdrant vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

A high-performance vector database with neural network or semantic-based matching

Spark SQL is a component on top of 'Spark Core' for structured data processing

Transactional SQL-on-Hadoop DBMS

Primary database model

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.esgyn.cn

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

github.com/qdrant/qdrant
qdrant.tech

spark.apache.org/sql

trafodion.apache.org

Technical documentation

qdrant.tech/documentation

spark.apache.org/docs/latest/sql-programming-guide.html

trafodion.apache.org/documentation.html

Developer

Esgyn

Rocket Software, originally Martin Phillips

Qdrant

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2015

1993

2021

2014

Current release

3.4-12

3.5.0 ( 2.13), September 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache 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

Rust

Scala

C++, Java

Server operating systems

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Docker
Linux
macOS
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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.

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Java
Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Collection-level replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

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

Access rights can be defined down to the item level

Key-based authentication

fine grained access rights according to SQL-standard

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