DBMS > Amazon Redshift vs. Cloudflare Workers KV vs. EsgynDB vs. HBase

System Properties Comparison Amazon Redshift vs. Cloudflare Workers KV vs. EsgynDB vs. HBase

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Wide-column store based on Apache Hadoop and on concepts of BigTable

Primary database model

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.39
Rank	#278	Overall
	#39	Key-value stores

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Website

aws.amazon.com/redshift

www.cloudflare.com/developer-platform/workers-kv

www.esgyn.cn

hbase.apache.org

Technical documentation

docs.aws.amazon.com/redshift

developers.cloudflare.com/kv/api

hbase.apache.org/book.html

Developer

Amazon (based on PostgreSQL)

Cloudflare

Esgyn

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Initial release

2012

2018

2015

2008

Current release

2.3.4, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

Java

Server operating systems

hosted

Linux

Linux
Unix
Windows

using Cygwin

Data scheme

yes

schema-free

yes

schema-free, schema definition possible

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

JDBC
ODBC

HTTP REST
Proprietary protocol

ADO.NET
JDBC
ODBC

Java API
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual 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

ACID

Single row ACID (across millions of columns)

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

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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