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DBMS > Amazon DocumentDB vs. Dgraph vs. FatDB vs. Google Cloud Datastore vs. Google Cloud Spanner

System Properties Comparison Amazon DocumentDB vs. Dgraph vs. FatDB vs. Google Cloud Datastore vs. Google Cloud Spanner

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDgraph  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDistributed and scalable native Graph DBMSA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.
Primary database modelDocument storeGraph DBMSDocument store
Key-value store
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Websiteaws.amazon.com/­documentdbdgraph.iocloud.google.com/­datastorecloud.google.com/­spanner
Technical documentationaws.amazon.com/­documentdb/­resourcesdgraph.io/­docscloud.google.com/­datastore/­docscloud.google.com/­spanner/­docs
DeveloperDgraph Labs, Inc.FatCloudGoogleGoogle
Initial release20192016201220082017
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC#
Server operating systemshostedLinux
OS X
Windows
Windowshostedhosted
Data schemeschema-freeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, details hereyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLnonono infoVia inetgration in SQL ServerSQL-like query language (GQL)yes infoQuery statements complying to ANSI 2011
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)GraphQL query language
gRPC (using protocol buffers) API
HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes infovia applicationsusing Google App Engineno
Triggersnonoyes infovia applicationsCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSynchronous replication via Raftselectable replication factorMulti-source replication using PaxosMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesyes infousing Google Cloud Dataflowyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate 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.Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes infovia ReferenceProperties or Ancestor pathsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoStrict serializable isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and rolesno infoPlanned for future releasesno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon DocumentDBDgraphFatDBGoogle Cloud DatastoreGoogle Cloud Spanner
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