DBMS > FoundationDB vs. Manticore Search vs. Riak KV vs. SQLite

System Properties Comparison FoundationDB vs. Manticore Search vs. Riak KV vs. SQLite

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

Distributed, fault tolerant key-value store

Widely used embeddable, in-process RDBMS

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Search engine

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

github.com/apple/foundationdb

manticoresearch.com

www.sqlite.org

Technical documentation

apple.github.io/foundationdb

manual.manticoresearch.com

www.tiot.jp/riak-docs/riak/kv/latest

www.sqlite.org/docs.html

Developer

FoundationDB

Manticore Software

OpenSource, formerly Basho Technologies

Dwayne Richard Hipp

Initial release

2013

2017

2009

2000

Current release

6.2.28, November 2020

6.0, February 2023

3.2.0, December 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

Apache version 2, commercial enterprise edition

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Erlang

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

Linux
OS X

server-less

Data scheme

schema-free

some layers support schemas

Fixed schema

schema-free

yes

dynamic column types

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

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

yes

full-text index on all search fields

restricted

yes

SQL

Support of SQL

supported in specific SQL layer only

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

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

HTTP API
Native Erlang Interface

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

in SQL-layer only

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Eventual Consistency

Foreign keys

Referential integrity

in SQL-layer only

links between data sets can be stored

yes

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

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes, using Riak Security

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