DBMS > Amazon Redshift vs. PouchDB vs. SwayDB vs. Vitess vs. XTDB

System Properties Comparison Amazon Redshift vs. PouchDB vs. SwayDB vs. Vitess vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

JavaScript DBMS with an API inspired by CouchDB

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

Scalable, distributed, cloud-native DBMS, extending MySQL

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

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

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/redshift

pouchdb.com

swaydb.simer.au

vitess.io

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

Technical documentation

docs.aws.amazon.com/redshift

pouchdb.com/guides

vitess.io/docs

www.xtdb.com/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Simer Plaha

The Linux Foundation, PlanetScale

Juxt Ltd.

Initial release

2012

2018

2013

2019

Current release

7.1.1, June 2019

15.0.2, December 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GNU Affero GPL V3.0

Open Source

Apache Version 2.0, commercial licenses available

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

JavaScript

Scala

Clojure

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Docker
Linux
macOS

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

Data scheme

yes

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

via views

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
MySQL protocol
ODBC

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript

Java
Kotlin
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

in Python

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of operations

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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