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DBMS > Google Cloud Bigtable vs. InterSystems Caché vs. Lovefield vs. Microsoft SQL Server

System Properties Comparison Google Cloud Bigtable vs. InterSystems Caché vs. Lovefield vs. Microsoft SQL Server

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A multi-model DBMS and application serverEmbeddable relational database for web apps written in pure JavaScriptMicrosofts flagship relational DBMS
Primary database modelKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Spatial 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
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Websitecloud.google.com/­bigtablewww.intersystems.com/­products/­cachegoogle.github.io/­lovefieldwww.microsoft.com/­en-us/­sql-server
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdlearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperGoogleInterSystemsGoogleMicrosoft
Initial release2015199720141989
Current release2018.1.4, May 20202.1.12, February 2017SQL Server 2022, November 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageJavaScriptC++
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
Windows
Data schemeschema-freedepending on used data modelyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.noyesnoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language infovia JavaScript builder patternyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScriptC#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoyesnoTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
TriggersnoyesUsing read-only observersyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenonetables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnoneyes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing MemoryDByes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesnofine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableInterSystems CachéLovefieldMicrosoft SQL Server
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