DBMS > Faircom DB vs. FatDB vs. MariaDB vs. Milvus vs. SWC-DB

System Properties Comparison Faircom DB vs. FatDB vs. MariaDB vs. Milvus vs. SWC-DB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

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

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store
Relational DBMS

Document store
Key-value store

Relational DBMS

Vector DBMS

Wide column store

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Time Series DBMS

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

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	93.81
Rank	#13	Overall
	#9	Relational DBMS

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Website

www.faircom.com/products/faircom-db

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

milvus.io

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

mariadb.com/kb/en/library

milvus.io/docs/overview.md

Developer

FairCom Corporation

FatCloud

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Alex Kashirin

Initial release

1979

2012

2009

Fork of MySQL, which was first released in 1995

2019

2020

Current release

V12, November 2020

11.3.2, February 2024

2.3.4, January 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Apache Version 2.0

Open Source

GPL V3

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

ANSI C, C++

C and C++

C++, Go

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

Data scheme

schema free, schema optional, schema required, partial schema,

schema-free

yes

Dynamic columns are supported

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

Via inetgration in SQL Server

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

C++

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

via applications

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

several options for horizontal partitioning and Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency
Immediate Consistency

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

not for in-memory storage engine

yes

In-memory capabilities

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

yes

with MEMORY storage engine

yes

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

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

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Highly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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Market metrics

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As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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Licensing and pricing models

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