DBMS > Fujitsu Enterprise Postgres vs. Milvus vs. MongoDB vs. searchxml

System Properties Comparison Fujitsu Enterprise Postgres vs. Milvus vs. MongoDB vs. searchxml

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Vector DBMS

Document store

Native XML DBMS
Search engine

Secondary database models

Document store
Spatial DBMS

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

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.postgresql.fastware.com

milvus.io

www.mongodb.com

www.searchxml.net/category/products

Technical documentation

www.postgresql.fastware.com/product-manuals

milvus.io/docs/overview.md

www.mongodb.com/docs/manual

www.searchxml.net/support/handouts

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

MongoDB, Inc

informationpartners gmbh

Initial release

2019

2009

2015

Current release

Fujitsu Enterprise Postgres 14, January 2022

2.3.4, January 2024

6.0.7, June 2023

1.0

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.

commercial

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

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

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Solaris
Windows

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.

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

on the application server

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

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.

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

yes

sychronisation to multiple collections

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

Immediate 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

ACID

Multi-document ACID Transactions with snapshot isolation

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Access rights for users and roles

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

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...
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

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

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

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

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

Core based licensing
» more

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

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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.