DBMS > Qdrant vs. ToroDB vs. Yaacomo

System Properties Comparison Qdrant vs. ToroDB vs. Yaacomo

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Vector DBMS

Document store

Relational DBMS

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

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Website

github.com/qdrant/qdrant
qdrant.tech

github.com/torodb/server

yaacomo.com

Technical documentation

qdrant.tech/documentation

Developer

Qdrant

8Kdata

Q2WEB GmbH

Initial release

2021

2016

2009

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL-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

Rust

Java

Server operating systems

Docker
Linux
macOS
Windows

All OS with a Java 7 VM

Android
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numbers, Strings, Geo, Boolean

yes

string, integer, double, boolean, date, object_id

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

yes

APIs and other access methods

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

JDBC
ODBC

Supported programming languages

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Collection-level replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency, tunable consistency

Eventual Consistency
Immediate 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

Key-based authentication

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant Raises $28M to Advance Massive-Scale AI Applications
23 January 2024, Business Wire

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, Oracle

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

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