DBMS > etcd vs. FeatureBase vs. Milvus vs. MongoDB vs. Rockset

System Properties Comparison etcd vs. FeatureBase vs. Milvus vs. MongoDB vs. Rockset

Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Relational DBMS
Search engine

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

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	410.24
Rank	#5	Overall
	#1	Document stores

Score	1.07
Rank	#180	Overall
	#31	Document stores

Website

etcd.io
github.com/etcd-io/etcd

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.featurebase.com

milvus.io/docs/overview.md

www.mongodb.com/docs/manual

docs.rockset.com

Developer

Molecula and Pilosa Open Source Contributors

MongoDB, Inc

Rockset

Initial release

2017

2019

2009

2019

Current release

3.4, August 2019

2022, May 2022

2.4.4, May 2024

7.0.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

yes

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

MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

C++, Go

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Solaris
Windows

hosted

Data scheme

schema-free

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL queries

Read-only SQL queries via the MongoDB Atlas SQL Interface

Read-only SQL queries, including JOINs

APIs and other access methods

gRPC
JSON over HTTP

gRPC
JDBC
Kafka Connector
ODBC

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP REST

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java
Python

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

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

yes, watching key changes

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

yes

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Role based access control and fine grained access rights

Access rights for users and roles

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.