DBMS > Apache Doris vs. Drizzle vs. EsgynDB vs. HEAVY.AI vs. TempoIQ

System Properties Comparison Apache Doris vs. Drizzle vs. EsgynDB vs. HEAVY.AI vs. TempoIQ

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

An MPP-based analytics DBMS embracing the MySQL protocol

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Time Series 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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

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

www.esgyn.cn

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

tempoiq.com (offline)

Technical documentation

github.com/apache/doris/wiki

docs.heavy.ai

Developer

Apache Software Foundation, originally contributed from Baidu

Drizzle project, originally started by Brian Aker

Esgyn

HEAVY.AI, Inc.

TempoIQ

Initial release

2017

2008

2015

2016

2012

Current release

1.2.2, February 2023

7.2.4, September 2012

5.10, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

C++, Java

C++ and CUDA

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

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

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
MySQL client

JDBC

ADO.NET
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

HTTP API

Supported programming languages

Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

hooks for callbacks inside the server can be used.

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Multi-source replication

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

simple authentication-based access control

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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