DBMS > Alibaba Cloud Table Store vs. Amazon Redshift vs. Apache Phoenix vs. HyperSQL

System Properties Comparison Alibaba Cloud Table Store vs. Amazon Redshift vs. Apache Phoenix vs. HyperSQL

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Large scale data warehouse service for use with business intelligence tools

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Wide column store

Relational DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/redshift

phoenix.apache.org

hsqldb.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/redshift

phoenix.apache.org

hsqldb.org/web/hsqlDocsFrame.html

Developer

Alibaba

Amazon (based on PostgreSQL)

Apache Software Foundation

Initial release

2016

2012

2014

2001

Current release

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

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

based on BSD 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

Server operating systems

hosted

Linux
Unix
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

HTTP API

JDBC
ODBC

JDBC

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

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

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

Atomic single-row operations

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

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

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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