DBMS > Apache Doris vs. DolphinDB vs. OpenMLDB vs. Snowflake

System Properties Comparison Apache Doris vs. DolphinDB vs. OpenMLDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

An open-source machine learning database that provides a feature platform for training and inference

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.dolphindb.com

openmldb.ai

www.snowflake.com

Technical documentation

github.com/apache/doris/wiki

docs.dolphindb.cn/en/help200/index.html

openmldb.ai/docs/zh/main

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from Baidu

DolphinDB, Inc

4 Paradigm Inc.

Snowflake Computing Inc.

Initial release

2017

2018

2020

2014

Current release

1.2.2, February 2023

v2.00.4, January 2022

2024-2 February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

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++, Java, Scala

Server operating systems

Linux

Linux
Windows

Linux

hosted

Data scheme

yes

Fixed schema

yes

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

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 query language

yes

APIs and other access methods

JDBC
MySQL client

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
SQLAlchemy

CLI Client
JDBC
ODBC

Supported programming languages

Java

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C++
Go
Java
Python
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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

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