DBMS > Apache Doris vs. Kinetica vs. Snowflake vs. TDSQL for MySQL

System Properties Comparison Apache Doris vs. Kinetica vs. Snowflake vs. TDSQL for MySQL

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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

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial 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	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

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

www.kinetica.com

www.snowflake.com

www.tencentcloud.com/products/dcdb

Technical documentation

github.com/apache/doris/wiki

docs.kinetica.com

docs.snowflake.net/manuals/index.html

www.tencentcloud.com/document/product/1042

Developer

Apache Software Foundation, originally contributed from Baidu

Kinetica

Snowflake Computing Inc.

Tencent

Initial release

2017

2012

2014

2013

Current release

1.2.2, February 2023

7.1, August 2021

License

Commercial or Open Source

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++

Server operating systems

Linux

hosted

Data scheme

yes

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

yes

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.

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

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Java

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

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

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

Multi-source replication
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

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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

Users with fine-grained authorization concept

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