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DBMS > Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Netezza vs. RavenDB

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. Netezza vs. RavenDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Database as a Service offering with high compatibility to Microsoft SQL ServerData warehouse and analytics appliance part of IBM PureSystemsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelKey-value store
Wide column store
Relational DBMSRelational DBMSDocument store
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitecloud.google.com/­bigtableazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.ibm.com/­products/­netezzaravendb.net
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlravendb.net/­docs
DeveloperGoogleMicrosoftIBMHibernating Rhinos
Initial release2015201020002010
Current releaseV125.4, July 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C#
Server operating systemshostedhostedLinux infoincluded in applianceLinux
macOS
Raspberry Pi
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesno
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.noyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyesyesSQL-like query language (RQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
.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 languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoTransact SQLyesyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes, with always 3 replicas availableSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate 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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID, 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.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardUsers with fine-grained authorization conceptAuthorization levels configured per client per database

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More resources
Google Cloud BigtableMicrosoft Azure SQL Database infoformerly SQL AzureNetezza infoAlso called PureData System for Analytics by IBMRavenDB
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