DBMS > EJDB vs. Galaxybase vs. GeoMesa vs. Milvus

System Properties Comparison EJDB vs. Galaxybase vs. GeoMesa vs. Milvus

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Scalable, ACID-compliant native distributed parallel graph platform

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

Primary database model

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Website

github.com/Softmotions/ejdb

galaxybase.com

www.geomesa.org

milvus.io

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

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

milvus.io/docs/overview.md

Developer

Softmotions

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

CCRi and others

Initial release

2012

2017

2014

2019

Current release

Nov 20, November 2021

5.0.0, May 2024

2.3.4, January 2024

License

Commercial or Open Source

Open Source

GPLv2

commercial

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

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

Scala

C++, Go

Server operating systems

server-less

Linux

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

Strong typed schema

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Vector, Numeric and String

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

in-process shared library

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

RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Go
Java
Python

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

Server-side scripts

Stored procedures

user defined procedures and functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Immediate Consistency

depending on storage layer

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

depending on storage layer

yes

User concepts

Access control

Role-based access control

yes

depending on the DBMS used for storage

Role based access control and fine grained access rights

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.

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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

show all

Recent citations in the news

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, ibm.com

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