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DBMS > Amazon DocumentDB vs. Citus vs. Google Cloud Bigtable vs. Google Cloud Datastore

System Properties Comparison Amazon DocumentDB vs. Citus vs. Google Cloud Bigtable vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelDocument storeRelational DBMSKey-value store
Wide column store
Document store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.47
Rank#76  Overall
#12  Document stores
Websiteaws.amazon.com/­documentdbwww.citusdata.comcloud.google.com/­bigtablecloud.google.com/­datastore
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.citusdata.comcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docs
DeveloperGoogleGoogle
Initial release2019201020152008
Current release8.1, December 2018
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availablecommercialcommercial
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.
Implementation languageC
Server operating systemshostedLinuxhostedhosted
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes, details here
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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsnoSQL-like query language (GQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nousing Google App Engine
TriggersnoyesnoCallbacks using the Google Apps Engine
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 replicasSource-replica replication infoother methods possible by using 3rd party extensionsInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)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.
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.nonono
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess 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 DocumentDBCitusGoogle Cloud BigtableGoogle Cloud Datastore
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