DBMS > Alibaba Cloud MaxCompute vs. Microsoft SQL Server vs. RDF4J vs. Solr vs. Sphinx

System Properties Comparison Alibaba Cloud MaxCompute vs. Microsoft SQL Server vs. RDF4J vs. Solr vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Microsofts flagship relational DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A widely used distributed, scalable search engine based on Apache Lucene

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Relational DBMS

RDF store

Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.alibabacloud.com/product/maxcompute

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

rdf4j.org

solr.apache.org

sphinxsearch.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

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

rdf4j.org/documentation

solr.apache.org/resources.html

sphinxsearch.com/docs

Developer

Alibaba

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Apache Software Foundation

Sphinx Technologies Inc.

Initial release

2016

1989

2004

2006

2001

Current release

SQL Server 2022, November 2022

9.6.0, April 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

hosted

Linux
Windows

Linux
OS X
Unix
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

RDF Schemas

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

yes

Solr Parallel SQL Interface

SQL-like query language (SphinxQL)

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Java API
RESTful HTTP/JSON API

Proprietary protocol

Supported programming languages

Java

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

Java
PHP
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Java

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

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

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