DBMS > Databend vs. Dgraph vs. EDB Postgres vs. Milvus vs. MongoDB

System Properties Comparison Databend vs. Dgraph vs. EDB Postgres vs. Milvus vs. MongoDB

Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Distributed and scalable native Graph DBMS

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

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

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	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Website

github.com/datafuselabs/databend
www.databend.com

Technical documentation

docs.databend.com

dgraph.io/docs

www.enterprisedb.com/docs

milvus.io/docs/overview.md

www.mongodb.com/docs/manual

Developer

Databend Labs

Dgraph Labs, Inc.

EnterpriseDB

MongoDB, Inc

Initial release

2021

2016

2005

2019

2009

Current release

1.0.59, April 2023

14, December 2021

2.3.4, January 2024

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

BSD for PostgreSQL-components

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.

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Implementation language

Rust

C++, Go

C++

Server operating systems

hosted
Linux
macOS

Linux
OS X
Windows

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
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

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

by hash, list or range

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

none

Synchronous replication via Raft

Multi-source replication

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

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

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

yes

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users with fine-grained authorization concept, user roles

Planned for future releases

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

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

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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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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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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