DBMS > Hypertable vs. Linter vs. MonetDB vs. Qdrant

System Properties Comparison Hypertable vs. Linter vs. MonetDB vs. Qdrant

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

RDBMS for high security requirements

A relational database management system that stores data in columns

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

Primary database model

Wide column store

Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

linter.ru

www.monetdb.org

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

www.monetdb.org/Documentation

qdrant.tech/documentation

Developer

Hypertable Inc.

relex.ru

MonetDB BV

Qdrant

Initial release

2009

1990

2004

2021

Current release

0.9.8.11, March 2016

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Rust

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

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

restricted

only exact value or prefix value scans

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

C++ API
Thrift

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

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

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Source-replica replication

none

Source-replica replication available in experimental status

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable 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

Key-based authentication

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