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DBMS > BigObject vs. Cachelot.io vs. Vitess

System Properties Comparison BigObject vs. Cachelot.io vs. Vitess

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCachelot.io  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesIn-memory caching systemScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedKey-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#342  Overall
#150  Relational DBMS
Score0.00
Rank#396  Overall
#64  Key-value stores
Score1.04
Rank#191  Overall
#89  Relational DBMS
Websitebigobject.iocachelot.iovitess.io
Technical documentationdocs.bigobject.iovitess.io/­docs
DeveloperBigObject, Inc.The Linux Foundation, PlanetScale
Initial release201520152013
Current release15.0.2, December 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoSimplified BSD LicenseOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Go
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
FreeBSD
Linux
OS X
Docker
Linux
macOS
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infowith proprietary extensions
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
Memcached protocolADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
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 proceduresLuanoyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemnonenoneEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnonoUsers with fine-grained authorization concept infono user groups or roles

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More resources
BigObjectCachelot.ioVitess
Recent citations in the 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



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