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

System Properties Comparison NSDb vs. OushuDB vs. Qdrant 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 data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

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

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

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

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

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

nsdb.io

www.oushu.com/product/oushuDB

github.com/qdrant/qdrant
qdrant.tech

swaydb.simer.au

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

Technical documentation

nsdb.io/Architecture

www.oushu.com/documentation

qdrant.tech/documentation

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

Developer

Oushu

Qdrant

Simer Plaha

Transaction Software GmbH

Initial release

2017

2021

2018

1987

Current release

4.0.1, August 2020

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

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

Scala

C and C++

Server operating systems

Linux
macOS

Linux

Docker
Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Scala

C
C++

.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

yes

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

Hadoop integration

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

Kerberos, SSL and role based access

Key-based authentication

fine grained access rights according to SQL-standard

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