DBMS > FoundationDB vs. Microsoft Azure Data Explorer vs. MySQL vs. SWC-DB

System Properties Comparison FoundationDB vs. Microsoft Azure Data Explorer vs. MySQL vs. SWC-DB

Please select another system to include it in the comparison.

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Fully managed big data interactive analytics platform

Widely used open source RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

column oriented

Relational DBMS

Key/Value like access via memcached API

Wide column store

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Spatial DBMS

Time Series 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	3.28
Rank	#83	Overall
	#45	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

github.com/apple/foundationdb

azure.microsoft.com/services/data-explorer

www.mysql.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

apple.github.io/foundationdb

docs.microsoft.com/en-us/azure/data-explorer

dev.mysql.com/doc

Developer

FoundationDB

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Alex Kashirin

Initial release

2013

2019

1995

2020

Current release

6.2.28, November 2020

cloud service with continuous releases

9.0.0, July 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

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 and C++

C++

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

some layers support schemas

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free

Typing

predefined data types such as float or date

some layers support typing

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

all fields are automatically indexed

yes

SQL

Support of SQL

supported in specific SQL layer only

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol
Thrift

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

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

C++

Server-side scripts

Stored procedures

in SQL-layer only

Yes, possible languages: KQL, Python, R

yes

proprietary syntax

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Eventual Consistency
Immediate 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

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Azure Active Directory Authentication

Users with fine-grained authorization concept

no user groups or roles

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.