DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon CloudSearch vs. Kinetica vs. Vitess

System Properties Comparison Amazon CloudSearch vs. Kinetica vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonKinetica  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudFully vectorized database across both GPUs and CPUsScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelSearch engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websiteaws.amazon.com/­cloudsearchwww.kinetica.comvitess.io
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.kinetica.comvitess.io/­docs
DeveloperAmazonKineticaThe Linux Foundation, PlanetScale
Initial release201220122013
Current release7.1, August 202115.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Go
Server operating systemshostedLinuxDocker
Linux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.no
Secondary indexesyes infoall search fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infowith proprietary extensions
APIs and other access methodsHTTP APIJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
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 proceduresnouser defined functionsyes infoproprietary syntax
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSSource-replica replicationMulti-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 Consistency or Eventual Consistency depending on configurationEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyes 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 datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users and roles on table levelUsers 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
Amazon CloudSearchKineticaVitess
DB-Engines blog posts

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Is Amazon CloudSearch superior to do-it-yourself search tools?
24 January 2014, TechTarget

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

Amazon Takes On Google And Microsoft With CloudSearch
16 April 2012, Forbes

Amazon CloudSearch – Even Better Searching for Less Than $100/Month | Amazon Web Services
24 March 2014, AWS Blog

provided by Google News

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

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

Milvus logo

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

Neo4j logo

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

Present your product here