DBMS > Apache Doris vs. HEAVY.AI vs. Lovefield vs. OpenQM

System Properties Comparison Apache Doris vs. HEAVY.AI vs. Lovefield vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

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

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

github.com/apache/doris/wiki

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation, originally contributed from Baidu

HEAVY.AI, Inc.

Google

Rocket Software, originally Martin Phillips

Initial release

2017

2016

2014

1993

Current release

1.2.2, February 2023

5.10, January 2022

2.1.12, February 2017

3.4-12

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++ and CUDA

JavaScript

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

with some exceptions

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

via JavaScript builder pattern

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC
Thrift
Vega

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Round robin

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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More resources

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