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DBMS > Drizzle vs. ObjectBox vs. TimescaleDB vs. Vitess

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

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonObjectBox  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSObject oriented DBMS
Vector DBMS
Time Series DBMSRelational DBMS
Secondary database modelsTime Series DBMSRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
#7  Vector DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitegithub.com/­objectbox
objectbox.io
www.timescale.comvitess.io
Technical documentationdocs.objectbox.iodocs.timescale.comvitess.io/­docs
DeveloperDrizzle project, originally started by Brian AkerObjectBox LimitedTimescaleThe Linux Foundation, PlanetScale
Initial release2008201720172013
Current release7.2.4, September 20124.0 (May 2024)2.15.0, May 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoGNU GPLBindings are released under Apache 2.0 infoApache License 2.0Open 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++CGo
Server operating systemsFreeBSD
Linux
OS X
Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Linux
OS X
Windows
Docker
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes, plus "flex" map-like typesnumerics, 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.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoyes infofull PostgreSQL SQL syntaxyes infowith proprietary extensions
APIs and other access methodsJDBCProprietary native APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C++
Java
PHP
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
.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 proceduresnonouser 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.noyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Data sync between devices allowing occasional connected databases to work completely offlineSource-replica replication with hot standby and reads on replicas infoMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesyesyesyes 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 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.nonoyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPyesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DrizzleObjectBoxTimescaleDBVitess
News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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More resources
DrizzleObjectBoxTimescaleDBVitess
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Recent citations in the news

ObjectBox Raises $2M in Funding
4 December 2018, FinSMEs

The Megashift Towards Decentralized Edge Computing
27 August 2021, hackernoon.com

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

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

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

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

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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

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

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

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

provided by Google News



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