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DBMS > Amazon CloudSearch vs. Kinetica vs. Pinecone

System Properties Comparison Amazon CloudSearch vs. Kinetica vs. Pinecone

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonKinetica  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudFully vectorized database across both GPUs and CPUsA managed, cloud-native vector database
Primary database modelSearch engineRelational DBMSVector DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websiteaws.amazon.com/­cloudsearchwww.kinetica.comwww.pinecone.io
Technical documentationdocs.aws.amazon.com/­cloudsearchdocs.kinetica.comdocs.pinecone.io/­docs/­overview
DeveloperAmazonKineticaPinecone Systems, Inc
Initial release201220122019
Current release7.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemshostedLinuxhosted
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyesString, Number, Boolean
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 indexesyes infoall search fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsno
APIs and other access methodsHTTP APIJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Python
Server-side scripts infoStored proceduresnouser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSSource-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 configuration
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 RAMno
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users and roles on table level

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More resources
Amazon CloudSearchKineticaPinecone
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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

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26 March 2024, Datanami

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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

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Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone Brings Serverless To Vector Databases
16 January 2024, Forbes

Pinecone: New vector database architecture a 'breakthrough' to curb AI hallucinations
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