DBMS > Apache Doris vs. Drizzle vs. EsgynDB vs. Google BigQuery vs. ObjectBox

System Properties Comparison Apache Doris vs. Drizzle vs. EsgynDB vs. Google BigQuery vs. ObjectBox

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

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

Large scale data warehouse service with append-only tables

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

Object oriented DBMS

Secondary database models

Time Series 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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

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

www.esgyn.cn

cloud.google.com/bigquery

objectbox.io

Technical documentation

github.com/apache/doris/wiki

cloud.google.com/bigquery/docs

docs.objectbox.io

Developer

Apache Software Foundation, originally contributed from Baidu

Drizzle project, originally started by Brian Aker

Esgyn

Google

ObjectBox Limited

Initial release

2017

2008

2015

2010

2017

Current release

1.2.2, February 2023

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

Open Source

Apache License 2.0

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 C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

hosted

Android
iOS
Linux
macOS
Windows

Data scheme

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

APIs and other access methods

JDBC
MySQL client

JDBC

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

Proprietary native API

Supported programming languages

Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

user defined functions

in JavaScript

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

online/offline synchronization between client and server

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

Since BigQuery is designed for querying 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.

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

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