DBMS > 4D vs. Apache IoTDB vs. Memcached vs. Microsoft SQL Server vs. Percona Server for MySQL

System Properties Comparison 4D vs. Apache IoTDB vs. Memcached vs. Microsoft SQL Server vs. Percona Server for MySQL

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

In-memory key-value store, originally intended for caching

Microsofts flagship relational DBMS

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Website

www.4d.com

iotdb.apache.org

www.memcached.org

www.microsoft.com/en-us/sql-server

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

Technical documentation

developer.4d.com

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

github.com/memcached/memcached/wiki

learn.microsoft.com/en-US/sql/sql-server

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

Developer

4D, Inc

Apache Software Foundation

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Percona

Initial release

1984

2018

2003

1989

2008

Current release

v20, April 2023

1.1.0, April 2023

1.6.25, March 2024

SQL Server 2022, November 2022

8.0.36-28, 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

BSD license

commercial

restricted free version is available

Open Source

GPL version 2

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

Java

C++

C and C++

Server operating systems

OS X
Windows

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

yes

close to SQL 92

SQL-like query language

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
Native API

Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

none

Repcached, a Memcached patch, provides this functionallity

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication
XtraDB Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Users and groups

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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.