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DBMS > Google Cloud Datastore vs. HBase vs. Microsoft Azure Table Storage vs. RavenDB

System Properties Comparison Google Cloud Datastore vs. HBase vs. Microsoft Azure Table Storage vs. RavenDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRavenDB  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 BigTableA Wide Column Store for rapid development using massive semi-structured datasetsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelDocument storeWide column storeWide column storeDocument store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series 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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score2.92
Rank#101  Overall
#18  Document stores
Websitecloud.google.com/­datastorehbase.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesravendb.net
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmlravendb.net/­docs
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftHibernating Rhinos
Initial release2008200820122010
Current release2.3.4, January 20215.4, July 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoAGPL version 3, commercial license available
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
macOS
Raspberry Pi
Windows
Data schemeschema-freeschema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereoptions to bring your own types, AVROyesno
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.nonono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoSQL-like query language (RQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
RESTful HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in Javanoyes
TriggersCallbacks using the Google Apps Engineyesnoyes
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 service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes
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 ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
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)optimistic lockingACID, Cluster-wide transaction available
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.noyesno
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 & ABACAccess rights based on private key authentication or shared access signaturesAuthorization levels configured per client per database

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More resources
Google Cloud DatastoreHBaseMicrosoft Azure Table StorageRavenDB
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