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DBMS > Amazon CloudSearch vs. Google Cloud Datastore vs. Pinecone

System Properties Comparison Amazon CloudSearch vs. Google Cloud Datastore vs. Pinecone

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA managed, cloud-native vector database
Primary database modelSearch engineDocument storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#133  Overall
#12  Search engines
Score4.13
Rank#71  Overall
#12  Document stores
Score3.02
Rank#87  Overall
#3  Vector DBMS
Websiteaws.amazon.com/­cloudsearchcloud.google.com/­datastorewww.pinecone.io
Technical documentationdocs.aws.amazon.com/­cloudsearchcloud.google.com/­datastore/­docsdocs.pinecone.io/­docs/­overview
DeveloperAmazonGooglePinecone Systems, Inc
Initial release201220082019
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemshostedhostedhosted
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereString, 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 query language (GQL)no
APIs and other access methodsHTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Python
Server-side scripts infoStored proceduresnousing Google App Engine
TriggersnoCallbacks using the Google Apps Engine
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 AWSMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.nono
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon CloudSearchGoogle Cloud DatastorePinecone
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