DBMS > Dragonfly vs. IBM Db2 vs. Milvus vs. searchxml

System Properties Comparison Dragonfly vs. IBM Db2 vs. Milvus vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Vector DBMS

Native XML DBMS
Search engine

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.ibm.com/products/db2

milvus.io

www.searchxml.net/category/products

Technical documentation

www.dragonflydb.io/docs

www.ibm.com/docs/en/db2

milvus.io/docs/overview.md

www.searchxml.net/support/handouts

Developer

DragonflyDB team and community contributors

IBM

informationpartners gmbh

Initial release

2023

1983

host version

2019

2015

Current release

1.0, March 2023

12.1, October 2016

2.3.4, January 2024

1.0

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

free version is available

Open Source

Apache Version 2.0

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.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++

C and C++

C++, Go

C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Windows

Data scheme

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Lua

yes

on the application server

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

with separate tools (MQ, InfoSphere)

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

Password-based authentication

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Domain, group and role-based access control at the document level and for application services

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

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