DBMS > FoundationDB vs. LeanXcale vs. Manticore Search vs. MySQL

System Properties Comparison FoundationDB vs. LeanXcale vs. Manticore Search vs. MySQL

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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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Multi-storage database for search, including full-text search.

Widely used open source RDBMS

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store
Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

github.com/apple/foundationdb

www.leanxcale.com

manticoresearch.com

www.mysql.com

Technical documentation

apple.github.io/foundationdb

manual.manticoresearch.com

dev.mysql.com/doc

Developer

FoundationDB

LeanXcale

Manticore Software

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2013

2015

2017

1995

Current release

6.2.28, November 2020

6.0, February 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL version 2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

C and C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

some layers support schemas

yes

Fixed schema

yes

Typing

predefined data types such as float or date

some layers support typing

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

through Apache Derby

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
Java
Scala

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

in SQL-layer only

user defined functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

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

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

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