DBMS > Apache Phoenix vs. MongoDB vs. YottaDB

System Properties Comparison Apache Phoenix vs. MongoDB vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store

Key-value store

Secondary database models

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

Relational DBMS

using the Octo plugin

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

Score	1.90
Rank	#121	Overall
	#59	Relational DBMS

Score	400.39
Rank	#5	Overall
	#1	Document stores

Score	0.23
Rank	#301	Overall
	#44	Key-value stores

Website

phoenix.apache.org

www.mongodb.com

yottadb.com

Technical documentation

phoenix.apache.org

www.mongodb.com/docs/manual

yottadb.com/resources/documentation

Developer

Apache Software Foundation

MongoDB, Inc

YottaDB, LLC

Initial release

2014

2009

2001

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

7.0.5, January 2024

License

Commercial or Open Source

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.

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java

C++

Server operating systems

Linux
Unix
Windows

Linux
OS X
Solaris
Windows

Docker
Linux

Data scheme

yes

late-bound, schema-on-read capabilities

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

by using the Octo plugin

APIs and other access methods

JDBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

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

Multi-source replication
Source-replica replication

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

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

yes

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users and roles

Users and groups based on OS-security mechanisms

More information provided by the system vendor

Specific characteristics

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

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

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

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

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

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