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DBMS > Google Cloud Datastore vs. HBase vs. Microsoft Azure AI Search vs. Sequoiadb

System Properties Comparison Google Cloud Datastore vs. HBase vs. Microsoft Azure AI Search vs. Sequoiadb

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTableSearch-as-a-service for web and mobile app developmentNewSQL database with distributed OLTP and SQL
Primary database modelDocument storeWide column storeSearch engineDocument store
Relational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score5.59
Rank#63  Overall
#7  Search engines
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitecloud.google.com/­datastorehbase.apache.orgazure.microsoft.com/­en-us/­services/­searchwww.sequoiadb.com
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmllearn.microsoft.com/­en-us/­azure/­searchwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftSequoiadb Ltd.
Initial release2008200820152013
Current release2.3.4, January 2021V1
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
hostedLinux
Data schemeschema-freeschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyes, details hereoptions to bring your own types, AVROyesyes infooid, date, timestamp, binary, regex
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 indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
RESTful HTTP APIproprietary protocol using JSON
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
Java
JavaScript
Python
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in JavanoJavaScript
TriggersCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud serviceSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)noDocument is locked during a transaction
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes infousing Azure authenticationsimple password-based access control

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More resources
Google Cloud DatastoreHBaseMicrosoft Azure AI SearchSequoiadb
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