DBMS > Apache Doris vs. Riak TS

System Properties Comparison Apache Doris vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Relational DBMS

Time Series DBMS

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Score	0.48
Rank	#250	Overall
	#116	Relational DBMS

Score	0.17
Rank	#319	Overall
	#27	Time Series DBMS

Website

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

Technical documentation

github.com/apache/doris/wiki

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation, originally contributed from Baidu

Open Source, formerly Basho Technologies

Initial release

2017

2015

Current release

1.2.2, February 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Erlang

Server operating systems

Linux

Linux
OS X

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

yes

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

JDBC
MySQL client

HTTP API
Native Erlang Interface

Supported programming languages

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

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

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

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