DBMS > Couchbase vs. Fauna vs. HEAVY.AI vs. Percona Server for MongoDB vs. Realm

System Properties Comparison Couchbase vs. Fauna vs. HEAVY.AI vs. Percona Server for MongoDB vs. Realm

Editorial information provided by DB-Engines

Name

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

www.couchbase.com

fauna.com

github.com/heavyai/heavydb
www.heavy.ai

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

realm.io

Technical documentation

docs.couchbase.com

docs.fauna.com

docs.heavy.ai

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

realm.io/docs

Developer

Couchbase, Inc.

Fauna, Inc.

HEAVY.AI, Inc.

Percona

Realm, acquired by MongoDB in May 2019

Initial release

2011

2014

2016

2015

2014

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

5.10, January 2022

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL Version 2

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Go and Erlang

Scala

C++ and CUDA

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

proprietary protocol using JSON

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

All languages supporting JDBC/ODBC/Thrift
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
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via the TAP protocol

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

horizontal partitioning

consistent hashing

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency
Immediate 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

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

Ephemeral buckets

yes

via In-Memory Engine

yes

In-Memory realm

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

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