DBMS > Amazon Redshift vs. Apache Doris vs. EventStoreDB vs. InfluxDB vs. Sequoiadb

System Properties Comparison Amazon Redshift vs. Apache Doris vs. EventStoreDB vs. InfluxDB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An MPP-based analytics DBMS embracing the MySQL protocol

Industrial-strength, open-source database solution built from the ground up for event sourcing.

DBMS for storing time series, events and metrics

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Event Store

Time Series DBMS

Document store
Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

aws.amazon.com/redshift

doris.apache.org
github.com/apache/doris

www.eventstore.com

www.influxdata.com/products/influxdb-overview

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/redshift

github.com/apache/doris/wiki

developers.eventstore.com

docs.influxdata.com/influxdb

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from Baidu

Event Store Limited

Sequoiadb Ltd.

Initial release

2012

2017

2012

2013

Current release

1.2.2, February 2023

21.2, February 2021

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Server: AGPL; Client: Apache V2

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

Java

C++

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X

through Homebrew

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

HTTP API
JSON over UDP

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

Java

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

in enterprise version only

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

in enterprise version only

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

ACID

Document is locked during a transaction

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

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

simple rights management via user accounts

simple password-based access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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