DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Drizzle vs. FatDB vs. TimescaleDB vs. Vitess

System Properties Comparison Drizzle vs. FatDB vs. TimescaleDB vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFatDB  Xexclude from comparisonTimescaleDB  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.FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A .NET NoSQL DBMS that can integrate with and extend SQL Server.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSDocument store
Key-value store
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Score1.04
Rank#191  Overall
#89  Relational DBMS
Websitewww.timescale.comvitess.io
Technical documentationdocs.timescale.comvitess.io/­docs
DeveloperDrizzle project, originally started by Brian AkerFatCloudTimescaleThe Linux Foundation, PlanetScale
Initial release2008201220172013
Current release7.2.4, September 20122.13.0, November 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen 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#CGo
Server operating systemsFreeBSD
Linux
OS X
WindowsLinux
OS X
Windows
Docker
Linux
macOS
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.yes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsno infoVia inetgration in SQL Serveryes infofull PostgreSQL SQL syntaxyes infowith proprietary extensions
APIs and other access methodsJDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C++
Java
PHP
C#.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
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 proceduresnoyes infovia applicationsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infoproprietary syntax
Triggersno infohooks for callbacks inside the server can be used.yes infovia applicationsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorSource-replica replication with hot standby and reads on replicas infoMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes 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.noyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardUsers 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
DrizzleFatDBTimescaleDBVitess
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

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

TimescaleDB for Azure Database for PostgreSQL to power IoT and time-series workloads | Azure updates
18 March 2019, Microsoft

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

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

Vitess, the database clustering system powering YouTube, graduates CNCF incubation
5 November 2019, SiliconANGLE News

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

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

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

provided by Google News



Share this page

Featured Products

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

SingleStore logo

The database to transact, analyze and contextualize your data in real time.
Try it today.

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

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Present your product here