DBMS > Oracle NoSQL vs. Percona Server for MongoDB vs. Quasardb vs. YottaDB

System Properties Comparison Oracle NoSQL vs. Percona Server for MongoDB vs. Quasardb vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Distributed, high-performance timeseries database

A fast and solid embedded Key-value store

Primary database model

Document store
Key-value store
Relational DBMS

Document store

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

www.oracle.com/database/nosql/technologies/nosql

www.percona.com/mongodb/software/percona-server-for-mongodb

quasar.ai

yottadb.com

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.percona.com/percona-distribution-for-mongodb

doc.quasar.ai/master

yottadb.com/resources/documentation

Developer

Oracle

Percona

quasardb

YottaDB, LLC

Initial release

2011

2015

2009

2001

Current release

23.3, December 2023

3.4.10-2.10, November 2017

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPL Version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPL 3.0

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.

Implementation language

Java

C++

Server operating systems

Linux
Solaris SPARC/x86

Linux

BSD
Linux
OS X
Windows

Docker
Linux

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

optional

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

by using the Octo plugin

APIs and other access methods

RESTful HTTP API

proprietary protocol using JSON

HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

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

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

Server-side scripts

Stored procedures

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

off heap cache

yes

via In-Memory Engine

yes

Transient mode

yes

User concepts

Access control

Access rights for users and roles

Cryptographically strong user authentication and audit trail

Users and groups based on OS-security mechanisms

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