DBMS > Amazon CloudSearch vs. Apache Phoenix vs. Citus vs. Microsoft SQL Server vs. RDF4J

System Properties Comparison Amazon CloudSearch vs. Apache Phoenix vs. Citus vs. Microsoft SQL Server vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

A scale-out RDBMS with evolutionary schema built on Apache HBase

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Microsofts flagship relational DBMS

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

Primary database model

Search engine

Relational DBMS

RDF store

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

aws.amazon.com/cloudsearch

phoenix.apache.org

www.citusdata.com

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

rdf4j.org

Technical documentation

docs.aws.amazon.com/cloudsearch

phoenix.apache.org

docs.citusdata.com

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

rdf4j.org/documentation

Developer

Amazon

Apache Software Foundation

Microsoft

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

Initial release

2012

2014

2010

1989

2004

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

8.1, December 2018

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

AGPL, commercial license also available

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux
Unix
Windows

Linux

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

RDF Schemas

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

APIs and other access methods

HTTP API

JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

yes

automatic partitioning across Amazon Search Instance as required

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

managed transparently by AWS

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

authentication via encrypted signatures

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

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