DBMS > Cachelot.io vs. EsgynDB vs. FoundationDB vs. Lovefield vs. MySQL

System Properties Comparison Cachelot.io vs. EsgynDB vs. FoundationDB vs. Lovefield vs. MySQL

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

In-memory caching system

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Ordered key-value store. Core features are complimented by layers.

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Primary database model

Key-value store

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Website

cachelot.io

www.esgyn.cn

github.com/apple/foundationdb

google.github.io/lovefield

www.mysql.com

Technical documentation

apple.github.io/foundationdb

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

Developer

Esgyn

FoundationDB

Google

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2015

2013

2014

1995

Current release

6.2.28, November 2020

2.1.12, February 2017

9.0.0, July 2024

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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

C++

C++, Java

C++

JavaScript

C and C++

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

some layers support typing

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

supported in specific SQL layer only

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

in SQL-layer only

yes

proprietary syntax

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

in SQL-layer only

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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