DBMS > 4D vs. Apache IoTDB vs. Greenplum vs. InterSystems Caché vs. Microsoft SQL Server

System Properties Comparison 4D vs. Apache IoTDB vs. Greenplum vs. InterSystems Caché vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

A multi-model DBMS and application server

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store

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	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.4d.com

iotdb.apache.org

greenplum.org

www.intersystems.com/products/cache

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

Technical documentation

developer.4d.com

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

docs.greenplum.org

docs.intersystems.com

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

Developer

4D, Inc

Apache Software Foundation

Pivotal Software Inc.

InterSystems

Microsoft

Initial release

1984

2018

2005

1997

1989

Current release

v20, April 2023

1.1.0, April 2023

7.0.0, September 2023

2018.1.4, May 2020

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

OS X
Windows

All OS with a Java VM (>= 1.8)

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

depending on used data model

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

since Version 4.2

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

JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Go
Java
Python
Scala

C
Java
Perl
Python
R

C#
C++
Java

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

Server-side scripts

Stored procedures

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

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

Source-replica replication

yes, but depending on the SQL-Server Edition

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

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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