DBMS > Apache IoTDB vs. FoundationDB vs. Microsoft Azure SQL Database vs. Percona Server for MySQL vs. RavenDB

System Properties Comparison Apache IoTDB vs. FoundationDB vs. Microsoft Azure SQL Database vs. Percona Server for MySQL vs. RavenDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

Database as a Service offering with high compatibility to Microsoft SQL Server

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Time Series DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

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

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	2.10
Rank	#119	Overall
	#57	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

iotdb.apache.org

github.com/apple/foundationdb

azure.microsoft.com/en-us/products/azure-sql/database

www.percona.com/software/mysql-database/percona-server

ravendb.net

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

apple.github.io/foundationdb

docs.microsoft.com/en-us/azure/azure-sql

www.percona.com/downloads/Percona-Server-LATEST

ravendb.net/docs

Developer

Apache Software Foundation

FoundationDB

Microsoft

Percona

Hibernating Rhinos

Initial release

2018

2013

2010

2008

2010

Current release

1.1.0, April 2023

6.2.28, November 2020

V12

8.0.36-28, 2024

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

GPL version 2

Open Source

AGPL version 3, commercial license available

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

Java

C++

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

hosted

Linux

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

schema-free

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

SQL-like query language

supported in specific SQL layer only

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
Native API

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

in SQL-layer only

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

yes, with always 3 replicas available

Multi-source replication
Source-replica replication
XtraDB Cluster

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Linearizable consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

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

yes

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Authorization levels configured per client per database

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