DBMS > Galaxybase vs. Milvus vs. NSDb vs. SwayDB vs. Transbase

System Properties Comparison Galaxybase vs. Milvus vs. NSDb vs. SwayDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

A DBMS designed for efficient storage of vector data and vector similarity searches

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

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	Graph DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

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

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

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

Technical documentation

milvus.io/docs/overview.md

nsdb.io/Architecture

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

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Simer Plaha

Transaction Software GmbH

Initial release

2017

2019

2017

2018

1987

Current release

Nov 20, November 2021

2.4.4, May 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C and Java

C++, Go

Java, Scala

Scala

C and C++

Server operating systems

Linux

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

Strong typed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
Python

C++
Go
Java
JavaScript (Node.js)
Python

Java
Scala

Java
Kotlin
Scala

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

Server-side scripts

Stored procedures

user defined procedures and functions

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

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

yes

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

Role-based access control

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

AI-Powered Search Engine With Milvus Vector Database on Vultr - SitePoint
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9 April 2024, ibm.com

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8 August 2024, TechTarget

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