DBMS > atoti vs. MonetDB vs. Qdrant vs. Sadas Engine

System Properties Comparison atoti vs. MonetDB vs. Qdrant vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A relational database management system that stores data in columns

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.59
Rank	#242	Overall
	#10	Object oriented DBMS

Score	1.72
Rank	#148	Overall
	#68	Relational DBMS

Score	1.23
Rank	#171	Overall
	#6	Vector DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

atoti.io

www.monetdb.org

github.com/qdrant/qdrant
qdrant.tech

www.sadasengine.com

Technical documentation

docs.atoti.io

www.monetdb.org/Documentation

qdrant.tech/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

ActiveViam

MonetDB BV

Qdrant

SADAS s.r.l.

Initial release

2004

2021

2006

Current release

Dec2023 (11.49), December 2023

8.0

License

Commercial or Open Source

commercial

free versions available

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

commercial

free trial version 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

Rust

C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

AIX
Linux
Windows

Data scheme

yes

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL 2003 with some extensions

yes

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Python

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding via remote tables

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Collection-level replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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, multi-version concurrency control (MVCC)

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Key-based authentication

Access rights for users, groups and roles according to SQL-standard

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