DBMS > Apache Doris vs. Drizzle vs. EsgynDB vs. TimescaleDB

System Properties Comparison Apache Doris vs. Drizzle vs. EsgynDB vs. TimescaleDB

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational 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	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

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

www.esgyn.cn

www.timescale.com

Technical documentation

github.com/apache/doris/wiki

docs.timescale.com

Developer

Apache Software Foundation, originally contributed from Baidu

Drizzle project, originally started by Brian Aker

Esgyn

Timescale

Initial release

2017

2008

2015

2017

Current release

1.2.2, February 2023

7.2.4, September 2012

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

Open Source

Apache 2.0

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

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

with proprietary extensions

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
MySQL client

JDBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Source-replica replication with hot standby and reads on replicas

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.

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

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

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

LLM-Powered OLAP: the Tencent Experience with Apache Doris
28 August 2023, hackernoon.com

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

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

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, azure.microsoft.com

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

provided by Google News

Share this page