DBMS > FileMaker vs. Microsoft SQL Server vs. Milvus vs. ObjectBox

System Properties Comparison FileMaker vs. Microsoft SQL Server vs. Milvus vs. ObjectBox

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Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Primary database model

Relational DBMS

Vector DBMS

Object oriented DBMS
Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Time Series DBMS

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

Score	45.20
Rank	#20	Overall
	#14	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Website

www.claris.com/filemaker

www.microsoft.com/en-us/sql-server

milvus.io

github.com/objectbox
objectbox.io

Technical documentation

www.claris.com/resources/documentation

learn.microsoft.com/en-US/sql/sql-server

milvus.io/docs/overview.md

docs.objectbox.io

Developer

Claris

a subsidiary of Apple

Microsoft

ObjectBox Limited

Initial release

1983

1989

2019

2017

Current release

19.4.1, November 2021

SQL Server 2022, November 2022

2.4.4, May 2024

4.0 (May 2024)

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

Bindings are released under Apache 2.0

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++

C++, Go

C and C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes, plus "flex" map-like types

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

Proprietary native API

Supported programming languages

PHP

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

yes, but depending on the SQL-Server Edition

Data sync between devices allowing occasional connected databases to work completely offline

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

yes

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

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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