DBMS > Apache Doris vs. Drizzle vs. EsgynDB vs. IBM Db2 Event Store

System Properties Comparison Apache Doris vs. Drizzle vs. EsgynDB vs. IBM Db2 Event Store

Please select another system to include it in the comparison.

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

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Relational DBMS

Event Store
Time Series DBMS

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

Score	0.69
Rank	#237	Overall
	#108	Relational DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

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

www.esgyn.cn

www.ibm.com/products/db2-event-store

Technical documentation

github.com/apache/doris/wiki

www.ibm.com/docs/en/db2-event-store

Developer

Apache Software Foundation, originally contributed from Baidu

Drizzle project, originally started by Brian Aker

Esgyn

IBM

Initial release

2017

2008

2015

2017

Current release

1.2.2, February 2023

7.2.4, September 2012

2.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

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

Linux, macOS, Windows for the developer addition

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

through the embedded Spark runtime

APIs and other access methods

JDBC
MySQL client

JDBC

ADO.NET
JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

No - written data is immutable

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

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

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

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

How Big Data Is Saving Lives in Real Time: IoV Data Analytics Helps Prevent Accidents
28 November 2023, KDnuggets

provided by Google News

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, IBM

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

Share this page