DBMS > FatDB vs. FoundationDB vs. H2 vs. Qdrant vs. SpatiaLite

System Properties Comparison FatDB vs. FoundationDB vs. H2 vs. Qdrant vs. SpatiaLite

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A high-performance vector database with neural network or semantic-based matching

Spatial extension of SQLite

Primary database model

Document store
Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Vector DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

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

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	1.56
Rank	#142	Overall
	#3	Spatial DBMS

Website

github.com/apple/foundationdb

www.h2database.com

github.com/qdrant/qdrant
qdrant.tech

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

apple.github.io/foundationdb

www.h2database.com/html/main.html

qdrant.tech/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

FatCloud

FoundationDB

Thomas Mueller

Qdrant

Alessandro Furieri

Initial release

2012

2013

2005

2021

2008

Current release

6.2.28, November 2020

2.2.220, July 2023

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Java

Rust

C++

Server operating systems

Windows

Linux
OS X
Windows

All OS with a Java VM

Docker
Linux
macOS
Windows

server-less

Data scheme

schema-free

some layers support schemas

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

some layers support typing

yes

Numbers, Strings, Geo, 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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

Via inetgration in SQL Server

supported in specific SQL layer only

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Java

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

via applications

in SQL-layer only

Java Stored Procedures and User-Defined Functions

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

Collection-level 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

Linearizable consistency

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

FoundationDB team’s new venture, Antithesis, raises $47M to enhance software testing
13 February 2024, SiliconANGLE News

Antithesis Launches Out Of Stealth To Revolutionize Software Reliability
13 February 2024, PR Newswire

Antithesis raises $47M to launch an automated testing platform for software
13 February 2024, TechCrunch

Apple Acquires FoundationDB
24 March 2015, blogs.wsj.com

Apple's FoundationDB takes new Record Layer open source, confirms tech underpins CloudKit
14 January 2019, AppleInsider

provided by Google News

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, businesswire.com

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

provided by Google News

Share this page