DBMS > 4D vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. LMDB vs. Microsoft SQL Server vs. Riak KV

System Properties Comparison 4D vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. LMDB vs. Microsoft SQL Server vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

A high performant, light-weight, embedded key-value database library

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

www.4d.com

www.alibabacloud.com/product/hybriddb-postgresql

www.symas.com/symas-embedded-database-lmdb

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

Technical documentation

developer.4d.com

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

www.lmdb.tech/doc

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

www.tiot.jp/riak-docs/riak/kv/latest

Developer

4D, Inc

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Symas

Microsoft

OpenSource, formerly Basho Technologies

Initial release

1984

2016

2011

1989

2009

Current release

v20, April 2023

0.9.32, January 2024

SQL Server 2022, November 2022

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Erlang

Server operating systems

OS X
Windows

hosted

Linux
Unix
Windows

Linux
Windows

Linux
OS X

Data scheme

yes

schema-free

yes

schema-free

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

restricted

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

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

HTTP API
Native Erlang Interface

Supported programming languages

4D proprietary IDE
PHP

C
Java
Perl
Python
R

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

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

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

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

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

none

yes, but depending on the SQL-Server Edition

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

fine grained access rights according to SQL-standard

yes, using Riak Security

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