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DBMS > Amazon DocumentDB vs. Google Cloud Datastore vs. NSDb vs. Oracle NoSQL

System Properties Comparison Amazon DocumentDB vs. Google Cloud Datastore vs. NSDb vs. Oracle NoSQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNSDb  Xexclude from comparisonOracle NoSQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelDocument storeDocument storeTime Series DBMSDocument store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastorensdb.iowww.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docsnsdb.io/­Architecturedocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperGoogleOracle
Initial release2019200820172011
Current release23.3, December 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ScalaJava
Server operating systemshostedhostedLinux
macOS
Linux
Solaris SPARC/x86
Data schemeschema-freeschema-freeSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or dateyesyes, details hereyes: int, bigint, decimal, stringoptional
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 indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC
HTTP REST
WebSocket
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
C
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication using PaxosElectable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infousing Google Cloud Dataflownowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Eventual ConsistencyEventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoconfigurable infoACID within a storage node (=shard)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infooff heap cache
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
Amazon DocumentDBGoogle Cloud DatastoreNSDbOracle NoSQL
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