DBMS > Kinetica vs. Milvus vs. Transbase vs. VelocityDB vs. VoltDB

System Properties Comparison Kinetica vs. Milvus vs. Transbase vs. VelocityDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

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

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

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.kinetica.com

milvus.io

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

velocitydb.com

www.voltdb.com

Technical documentation

docs.kinetica.com

milvus.io/docs/overview.md

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

velocitydb.com/UserGuide

docs.voltdb.com

Developer

Kinetica

Transaction Software GmbH

VelocityDB Inc

VoltDB Inc.

Initial release

2012

2019

1987

2011

2010

Current release

7.1, August 2021

2.4.4, May 2024

Transbase 8.3, 2022

7.x

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free development license

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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, C++

C++, Go

C and C++

Java, C++

Server operating systems

Linux

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
macOS
Solaris
Windows

Any that supports .NET

Linux
OS X

for development

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and 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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.Net

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

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

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

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Java

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
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 or Eventual Consistency depending on configuration

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

Based on Windows Authentication

Users and roles with access to stored procedures

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

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