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DBMS > Google Search Appliance vs. HBase vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

System Properties Comparison Google Search Appliance vs. HBase vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameGoogle Search Appliance  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionThe Google Search Appliance consists of hardware and software for indexing documents in local networks.Wide-column store based on Apache Hadoop and on concepts of BigTableGlobally distributed, horizontally scalable, multi-model database serviceA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelSearch engineWide column storeDocument store
Graph DBMS
Key-value store
Wide column store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.77
Rank#94  Overall
#10  Search engines
Score53.84
Rank#21  Overall
#2  Wide column stores
Score31.98
Rank#24  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score5.00
Rank#65  Overall
#5  Wide column stores
Websiteenterprise.google.com/­search/­products/­gsa.htmlhbase.apache.orgazure.microsoft.com/­services/­cosmos-dbazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationsupport.google.com/­gsahbase.apache.orgdocs.microsoft.com/­en-us/­azure/­cosmos-db
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftMicrosoft
Initial release2002200820142012
Current release2.2.0, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsLinux
Unix
Windows infousing Cygwin
hostedhosted
Data schemeschema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or dateoptions to bring your own types, AVROyes infoJSON typesyes
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 indexesnoyes infoAll properties auto-indexed by defaultno
SQL infoSupport of SQLnonoSQL-like query languageno
APIs and other access methodsAdministrative API
Browser interface
HTTP API
Java API
RESTful HTTP API
Thrift
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
RESTful HTTP API
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoCoprocessors in JavaJavaScriptno
TriggersyesJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMaster-master replication
Master-slave replication
yes infoImplicit feature of the cloud serviceyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyeswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataSingle row ACID (across millions of columns)Multi-item ACID transactions with snapshot isolation within a partitionoptimistic 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 controlUser authentication via various security protocolsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights can be defined down to the item levelAccess rights based on private key authentication or shared access signatures

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More resources
Google Search ApplianceHBaseMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBMicrosoft Azure Table Storage
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