DBMS > NSDb vs. Qdrant vs. SpatiaLite vs. SwayDB vs. Transbase

System Properties Comparison NSDb vs. Qdrant vs. SpatiaLite vs. SwayDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Spatial extension of SQLite

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	1.56
Rank	#142	Overall
	#3	Spatial DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

nsdb.io

github.com/qdrant/qdrant
qdrant.tech

www.gaia-gis.it/fossil/libspatialite/index

swaydb.simer.au

www.transaction.de/en/products/transbase.html

Technical documentation

nsdb.io/Architecture

qdrant.tech/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

www.transaction.de/en/products/transbase/features.html

Developer

Qdrant

Alessandro Furieri

Simer Plaha

Transaction Software GmbH

Initial release

2017

2021

2008

2018

1987

Current release

5.0.0, August 2020

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

GNU Affero GPL V3.0

commercial

free development license

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, Scala

Rust

C++

Scala

C and C++

Server operating systems

Linux
macOS

Docker
Linux
macOS
Windows

server-less

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Scala

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

Java
Kotlin
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Collection-level replication

none

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

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

Atomic execution of operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Using Apache Lucene

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

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

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

provided by Google News

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