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DBMS > Google Cloud Spanner vs. HBase vs. Hive vs. Microsoft Azure Table Storage

System Properties Comparison Google Cloud Spanner vs. HBase vs. Hive vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionA 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.Wide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSWide column storeRelational DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitecloud.google.com/­spannerhbase.apache.orghive.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­spanner/­docshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release2017200820122012
Current release2.3.4, January 20213.1.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VMhosted
Data schemeyesschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011noSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceno
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
selectable replication factoryes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationSingle row ACID (across millions of columns)nooptimistic locking
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 for users, groups and rolesAccess rights based on private key authentication or shared access signatures

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More resources
Google Cloud SpannerHBaseHiveMicrosoft Azure Table Storage
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