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DBMS > Apache Doris vs. Drizzle vs. EsgynDB vs. Transwarp KunDB vs. Vitess

System Properties Comparison Apache Doris vs. Drizzle vs. EsgynDB vs. Transwarp KunDB vs. Vitess

Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonDrizzle  Xexclude from comparisonEsgynDB  Xexclude from comparisonTranswarp KunDB  Xexclude from comparisonVitess  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOLTP DBMS based on a distributed architecture and highly compatible with MySQL and OracleScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.10
Rank#344  Overall
#151  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.esgyn.cnwww.transwarp.cn/­en/­product/­kundbvitess.io
Technical documentationgithub.com/­apache/­doris/­wikivitess.io/­docs
DeveloperApache Software Foundation, originally contributed from BaiduDrizzle project, originally started by Brian AkerEsgynTranswarpThe Linux Foundation, PlanetScale
Initial release2017200820152013
Current release1.2.2, February 20237.2.4, September 201215.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++, JavaGo
Server operating systemsLinuxFreeBSD
Linux
OS X
LinuxDocker
Linux
macOS
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsyesyesyes infowith proprietary extensions
APIs and other access methodsJDBC
MySQL client
JDBCADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJavaC
C++
Java
PHP
All languages supporting JDBC/ODBC/ADO.NetAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Proceduresyesyes infoproprietary syntax
Triggersnono infohooks for callbacks inside the server can be used.noyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyesyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardyesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache DorisDrizzleEsgynDBTranswarp KunDBVitess
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Recent citations in the news

Streamlining Data Operations: How a Grocery Chain Optimizes Workloads with Apache Doris
16 May 2024, hackernoon.com

Using Arrow Flight SQL Protocol in Apache Doris 2.1 For Super Fast Data Transfer
8 May 2024, hackernoon.com

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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PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

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