DBMS > Alibaba Cloud Table Store vs. Amazon Redshift vs. SwayDB vs. XTDB

System Properties Comparison Alibaba Cloud Table Store vs. Amazon Redshift vs. SwayDB vs. XTDB

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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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

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

Primary database model

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/redshift

swaydb.simer.au

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

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/redshift

www.xtdb.com/docs

Developer

Alibaba

Amazon (based on PostgreSQL)

Simer Plaha

Juxt Ltd.

Initial release

2016

2012

2018

2019

Current release

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GNU Affero GPL V3.0

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

Scala

Clojure

Server operating systems

hosted

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

Data scheme

schema-free

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC

Java
Kotlin
Scala

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

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

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

Atomic single-row operations

ACID

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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.

yes

User concepts

Access control

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

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