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DBMS > Amazon DocumentDB vs. Datastax Enterprise vs. Microsoft Azure AI Search vs. Pinecone

System Properties Comparison Amazon DocumentDB vs. Datastax Enterprise vs. Microsoft Azure AI Search vs. Pinecone

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.Search-as-a-service for web and mobile app developmentA managed, cloud-native vector database
Primary database modelDocument storeWide column storeSearch engineVector DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score4.82
Rank#65  Overall
#4  Wide column stores
Score5.75
Rank#58  Overall
#7  Search engines
Score3.02
Rank#87  Overall
#3  Vector DBMS
Websiteaws.amazon.com/­documentdbwww.datastax.com/­products/­datastax-enterpriseazure.microsoft.com/­en-us/­services/­searchwww.pinecone.io
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.datastax.comlearn.microsoft.com/­en-us/­azure/­searchdocs.pinecone.io/­docs/­overview
DeveloperDataStaxMicrosoftPinecone Systems, Inc
Initial release2019201120152019
Current release6.8, April 2020V1
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJava
Server operating systemshostedLinux
OS X
hostedhosted
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesString, 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.nononono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statements (CQL); Spark SQLnono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
RESTful HTTP APIRESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Python
Python
Server-side scripts infoStored proceduresnonono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infono "single point of failure"Sharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasconfigurable replication factor, datacenter aware, advanced replication for edge computingyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsno infoAtomicity and isolation are supported for single operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per objectyes infousing Azure authentication
More information provided by the system vendor
Amazon DocumentDBDatastax EnterpriseMicrosoft Azure AI SearchPinecone
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Amazon DocumentDBDatastax EnterpriseMicrosoft Azure AI SearchPinecone
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