DBMS > Apache Doris vs. Kinetica vs. RisingWave vs. Snowflake

System Properties Comparison Apache Doris vs. Kinetica vs. RisingWave vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Fully vectorized database across both GPUs and CPUs

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.kinetica.com

www.risingwave.com/database

www.snowflake.com

Technical documentation

github.com/apache/doris/wiki

docs.kinetica.com

docs.risingwave.com/docs/current/intro

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from Baidu

Kinetica

RisingWave Labs

Snowflake Computing Inc.

Initial release

2017

2012

2022

2014

Current release

1.2.2, February 2023

7.1, August 2021

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

Rust

Server operating systems

Linux

Docker
Linux
macOS

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC
RESTful HTTP API

JDBC
PostgreSQL wire protocol

CLI Client
JDBC
ODBC

Supported programming languages

Java

C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

UDFs in Python or Java

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Users and Roles

Users with fine-grained authorization concept, user roles and pluggable authentication

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