DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > DuckDB vs. Percona Server for MySQL vs. Spark SQL vs. Vitess

System Properties Comparison DuckDB vs. Percona Server for MySQL vs. Spark SQL vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonPercona Server for MySQL  Xexclude from comparisonSpark SQL  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSEnhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.Spark SQL is a component on top of 'Spark Core' for structured data processingScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score2.10
Rank#119  Overall
#57  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websiteduckdb.orgwww.percona.com/­software/­mysql-database/­percona-serverspark.apache.org/­sqlvitess.io
Technical documentationduckdb.org/­docswww.percona.com/­downloads/­Percona-Server-LATESTspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvitess.io/­docs
DeveloperPerconaApache Software FoundationThe Linux Foundation, PlanetScale
Initial release2018200820142013
Current release1.0.0, June 20248.0.36-28, 20243.5.0 ( 2.13), September 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoGPL version 2Open Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++ScalaGo
Server operating systemsserver-lessLinuxLinux
OS X
Windows
Docker
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesno
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsyes infowith proprietary extensions
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Ada
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 proceduresnoyesnoyes infoproprietary syntax
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
XtraDB Cluster
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlnoUsers with fine-grained authorization concept infono user groups or rolesnoUsers with fine-grained authorization concept infono user groups or roles

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
DuckDBPercona Server for MySQLSpark SQLVitess
Recent citations in the news

DuckDB promises greater stability with 1.0 release
5 June 2024, The Register

DuckDB 1.0 Released
4 June 2024, iProgrammer

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

DuckDB: In-Process Python Analytics for Not-Quite-Big Data
31 May 2024, The New Stack

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

provided by Google News

Update or migrate? Planning for MySQL 5.7 EOL
22 June 2023, InfoWorld

Sizing Up Servers: Intel's Skylake-SP Xeon versus AMD's EPYC 7000 - The Server CPU Battle of the Decade?
11 July 2017, AnandTech

ScaleFlux computational storage makes Percona MySQL faster – Blocks and Files
5 August 2020, Blocks and Files

How to deploy the Percona database performance monitor with Docker
24 February 2023, TechRepublic

Supercharge your Amazon RDS for MySQL deployment with ProxySQL and Percona Monitoring and Management ...
12 October 2018, AWS Blog

provided by Google News

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

provided by Google News

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

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

PlanetScale Serves up Vitess-Powered Serverless MySQL
23 November 2021, The New Stack

PlanetScale offers undo button to reverse schema migration without losing data
24 March 2022, The Register

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

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here