DBMS > DataFS vs. Firebird vs. Milvus vs. ObjectBox vs. Trafodion

System Properties Comparison DataFS vs. Firebird vs. Milvus vs. ObjectBox vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Firebird is an open source RDBMS forked from Borland's InterBase

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

Extremely fast embedded database for small devices, IoT and Mobile

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Graph DBMS

Time Series DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

Technical documentation

dev.mobiland.com/Overview.xsp

www.firebirdsql.org/en/reference-manuals

milvus.io/docs/overview.md

docs.objectbox.io

trafodion.apache.org/documentation.html

Developer

Mobiland AG

Firebird Foundation

ObjectBox Limited

Apache Software Foundation, originally developed by HP

Initial release

2018

2000

As fork of Borland's InterBase

2019

2017

2014

Current release

1.1.263, October 2022

5.0.0, January 2024

2.3.4, January 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache 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 and C++

C++, Go

C and C++

C++, Java

Server operating systems

Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Android
iOS
Linux
macOS
Windows

Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

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

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP API

Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

PSQL

Java Stored Procedures

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

online/offline synchronization between client and server

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

Features a multi-generational MVCC architecture, readers do not block writers

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

Windows-Profile

Users with fine-grained authorization concept

Role based access control and fine grained access rights

yes

fine grained access rights according to SQL-standard

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

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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

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