DBMS > Amazon Redshift vs. Databend vs. etcd vs. Hawkular Metrics

System Properties Comparison Amazon Redshift vs. Databend vs. etcd vs. Hawkular Metrics

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

A distributed reliable key-value store

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Website

aws.amazon.com/redshift

github.com/datafuselabs/databend
www.databend.com

etcd.io
github.com/etcd-io/etcd

www.hawkular.org

Technical documentation

docs.aws.amazon.com/redshift

docs.databend.com

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Amazon (based on PostgreSQL)

Databend Labs

Community supported by Red Hat

Initial release

2012

2021

2014

Current release

1.0.59, April 2023

3.4, August 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Rust

Java

Server operating systems

hosted

hosted
Linux
macOS

FreeBSD
Linux
Windows

experimental

Linux
OS X
Windows

Data scheme

yes

schema-free

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

CLI Client
JDBC
RESTful HTTP API

gRPC
JSON over HTTP

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes, watching key changes

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

ACID

yes

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

Users with fine-grained authorization concept, user roles

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