DBMS > Infobright vs. MonetDB vs. Qdrant vs. SWC-DB

System Properties Comparison Infobright vs. MonetDB vs. Qdrant vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A relational database management system that stores data in columns

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

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Vector DBMS

Wide column store

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

ignitetech.com/softwarelibrary/infobrightdb

www.monetdb.org

github.com/qdrant/qdrant
qdrant.tech

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

www.monetdb.org/Documentation

qdrant.tech/documentation

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

MonetDB BV

Qdrant

Alex Kashirin

Initial release

2005

2004

2021

2020

Current release

Dec2023 (11.49), December 2023

0.5, April 2021

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

Open Source

GPL V3

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

Rust

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Knowledge Grid Technology used instead

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

SQL 2003 with some extensions

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Proprietary protocol
Thrift

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

C++

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication available in experimental status

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

Key-based authentication

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