DBMS > Dragonfly vs. Ehcache vs. GeoMesa vs. Milvus vs. VelocityDB

System Properties Comparison Dragonfly vs. Ehcache vs. GeoMesa vs. Milvus vs. VelocityDB

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

A widely adopted Java cache with tiered storage options

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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

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

Primary database model

Key-value store

Spatial DBMS

Vector DBMS

Graph DBMS
Object oriented DBMS

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

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

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

Technical documentation

www.dragonflydb.io/docs

www.ehcache.org/documentation

www.geomesa.org/documentation/stable/user/index.html

milvus.io/docs/overview.md

velocitydb.com/UserGuide

Developer

DragonflyDB team and community contributors

Terracotta Inc, owned by Software AG

CCRi and others

VelocityDB Inc

Initial release

2023

2009

2014

2019

2011

Current release

1.0, March 2023

3.10.0, March 2022

4.0.5, February 2024

2.3.4, January 2024

7.x

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache License 2.0

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++

Java

Scala

C++, Go

Server operating systems

Linux

All OS with a Java VM

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Any that supports .NET

Data scheme

scheme-free

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JCache

RESTful HTTP API

.Net

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

Java

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

.Net

Server-side scripts

Stored procedures

Lua

Triggers

publish/subscribe channels provide some trigger functionality

yes

Cache Event Listeners

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

by using Terracotta Server

depending on storage layer

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Tunable Consistency (Strong, Eventual, Weak)

depending on storage layer

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

depending on storage layer

yes

User concepts

Access control

Password-based authentication

yes

depending on the DBMS used for storage

Role based access control and fine grained access rights

Based on Windows Authentication

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

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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

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Vector databases
2 June 2023, Matthias Gelbmann

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