DBMS > FileMaker vs. Milvus vs. MongoDB

System Properties Comparison FileMaker vs. Milvus vs. MongoDB

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Editorial information provided by DB-Engines

Name

Description

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

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

Primary database model

Relational DBMS

Search engine

Document store

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

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

Score	51.15
Rank	#22	Overall
	#15	Relational DBMS

Score	0.80
Rank	#239	Overall
	#16	Search engines

Score	458.78
Rank	#5	Overall
	#1	Document stores

Website

www.claris.com/filemaker

milvus.io

www.mongodb.com

Technical documentation

www.claris.com/resources/documentation

milvus.io/docs/overview.md

docs.mongodb.com/manual

Developer

FileMaker

a subsidiary of Apple

MongoDB, Inc

Initial release

1983

2019

2009

Current release

19.4.1, November 2021

2.2, November 2022

6.0.1, August 2022

License

Commercial or Open Source

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.

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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

ScaleGrid for MongoDB Database: Fully managed hosting for MongoDB Database on a wide variety of cloud providers and On-Premises. Automate your management, scaling and backups through one centralized platform.

Implementation language

C++, Go

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Solaris
Windows

Data scheme

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.

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

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

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

A http query request can return the data in XML format

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

Read-only SQL queries via the MongoDB Connector for BI

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

PHP

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
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

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

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.

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

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

simple rights management via user accounts and connection to external directory services

Access rights for users and roles

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...
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Typical application scenarios

Video media : video understanding, video deduplication. E-commerce and mobile applications...
» more

Key customers

Milvus is trusted by over 1,000 enterprises, including Baidu, eBay, IKEA, LINE, Shopee,...
» more

Market metrics

As of February 2023, 14k+ GitHub stars 2M+ downloads and installations 1000+ enterprise...
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Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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