DBMS > Alibaba Cloud MaxCompute vs. Elasticsearch vs. Microsoft SQL Server vs. RDF4J vs. XTDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Elasticsearch vs. Microsoft SQL Server vs. RDF4J vs. XTDB

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Microsofts flagship relational DBMS

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

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

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph 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	135.35
Rank	#7	Overall
	#1	Search engines

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.alibabacloud.com/product/maxcompute

www.elastic.co/elasticsearch

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

rdf4j.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

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

rdf4j.org/documentation

www.xtdb.com/docs

Developer

Alibaba

Elastic

Microsoft

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

Juxt Ltd.

Initial release

2016

2010

1989

2004

2019

Current release

8.6, January 2023

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Elastic License

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Clojure

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

Linux
OS X
Unix
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL

Support of SQL

SQL-like query language

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Java API
RESTful HTTP/JSON API

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

HTTP REST
JDBC

Supported programming languages

Java

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

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

Java
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in Java

yes

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

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

yes, but depending on the SQL-Server Edition

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate 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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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