DBMS > Apache Doris vs. Coveo vs. Drizzle vs. EsgynDB vs. Machbase Neo

System Properties Comparison Apache Doris vs. Coveo vs. Drizzle vs. EsgynDB vs. Machbase Neo

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.

Description

An MPP-based analytics DBMS embracing the MySQL protocol

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

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

TimeSeries DBMS for AIoT and BigData

Primary database model

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Website

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

www.coveo.com

www.esgyn.cn

machbase.com

Technical documentation

github.com/apache/doris/wiki

docs.coveo.com

machbase.com/dbms

Developer

Apache Software Foundation, originally contributed from Baidu

Coveo

Drizzle project, originally started by Brian Aker

Esgyn

Machbase

Initial release

2017

2012

2008

2015

2013

Current release

1.2.2, February 2023

7.2.4, September 2012

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GNU GPL

commercial

free test version available

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

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X

Linux

Linux
macOS
Windows

Data scheme

yes

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC
MySQL client

RESTful HTTP API

JDBC

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

Java

C#
Java
JavaScript
Python

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

selectable replication factor

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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

granular access controls, API key management, content filters

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

simple password-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

show all

Recent citations in the news

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

Streamlining Data Operations: How a Grocery Chain Optimizes Workloads with Apache Doris
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How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Data Analytics: Apache Doris' Impact in Reporting, Tagging, and Data Lake Operations
8 January 2024, hackernoon.com

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