DBMS > BoltDB vs. gStore vs. Lovefield vs. Milvus

System Properties Comparison BoltDB vs. gStore vs. Lovefield vs. Milvus

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

A native Graph DBMS to store and maintain very large RDF datasets.

Embeddable relational database for web apps written in pure JavaScript

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	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

github.com/boltdb/bolt

en.gstore.cn

google.github.io/lovefield

milvus.io

Technical documentation

en.gstore.cn/#/enDocs

github.com/google/lovefield/blob/master/docs/spec_index.md

milvus.io/docs/overview.md

Developer

Google

Initial release

2013

2016

2014

2019

Current release

1.2, November 2023

2.1.12, February 2017

2.3.4, January 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

BSD

Open Source

Apache 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++

JavaScript

C++, Go

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

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

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

HTTP API
SPARQL 1.1

RESTful HTTP API

Supported programming languages

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

JavaScript

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

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

What I learnt from building 3 high traffic web applications on an embedded key value store.
21 February 2018, hackernoon.com

4 Instructive Postmortems on Data Downtime and Loss
1 March 2024, The Hacker News

Three Reasons DevOps Should Consider Rocky Linux 9.4
15 May 2024, DevOps.com

Roblox’s cloud-native catastrophe: A post mortem
31 January 2022, InfoWorld

How to Put a GUI on Ansible, Using Semaphore
22 April 2023, The New Stack

provided by Google 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

provided by Google News

Share this page