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DBMS > Amazon DocumentDB vs. Apache Phoenix vs. Google Cloud Datastore vs. IBM Db2 warehouse

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. Google Cloud Datastore vs. IBM Db2 warehouse

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCloud-based data warehousing service
Primary database modelDocument storeRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score1.26
Rank#162  Overall
#73  Relational DBMS
Websiteaws.amazon.com/­documentdbphoenix.apache.orgcloud.google.com/­datastorewww.ibm.com/­products/­db2/­warehouse
Technical documentationaws.amazon.com/­documentdb/­resourcesphoenix.apache.orgcloud.google.com/­datastore/­docs
DeveloperApache Software FoundationGoogleIBM
Initial release2019201420082014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial
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 languageJava
Server operating systemshostedLinux
Unix
Windows
hostedhosted
Data schemeschema-freeyes infolate-bound, schema-on-read capabilitiesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, 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 infoImport/export of XML data possible
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Server-side scripts infoStored proceduresnouser defined functionsusing Google App EnginePL/SQL, SQL PL
TriggersnonoCallbacks using the Google Apps Engineyes
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
Source-replica replication
Multi-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Hadoop integrationyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual 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.Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBApache PhoenixGoogle Cloud DatastoreIBM Db2 warehouse infoformerly named IBM dashDB
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