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DBMS > Google BigQuery vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Netezza

System Properties Comparison Google BigQuery vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB vs. Netezza

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesSearch-as-a-service for web and mobile app developmentGlobally distributed, horizontally scalable, multi-model database serviceData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsVector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitecloud.google.com/­bigqueryazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­services/­cosmos-dbwww.ibm.com/­products/­netezza
Technical documentationcloud.google.com/­bigquery/­docslearn.microsoft.com/­en-us/­azure/­searchlearn.microsoft.com/­azure/­cosmos-db
DeveloperGoogleMicrosoftMicrosoftIBM
Initial release2010201520142000
Current releaseV1
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Server operating systemshostedhostedhostedLinux infoincluded in appliance
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes 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.nono
Secondary indexesnoyesyes infoAll properties auto-indexed by defaultyes
SQL infoSupport of SQLyesnoSQL-like query languageyes
APIs and other access methodsRESTful HTTP/JSON APIRESTful HTTP APIDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
JDBC
ODBC
OLE DB
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
Java
JavaScript
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnoJavaScriptyes
TriggersnonoJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud serviceSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*yes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying datanoMulti-item ACID transactions with snapshot isolation within a partitionACID
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.nono
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)yes infousing Azure authenticationAccess rights can be defined down to the item levelUsers with fine-grained authorization concept

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More resources
Google BigQueryMicrosoft Azure AI SearchMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBNetezza infoAlso called PureData System for Analytics by IBM
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