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DBMS > Google BigQuery vs. InterSystems Caché vs. Microsoft SQL Server vs. RavenDB

System Properties Comparison Google BigQuery vs. InterSystems Caché vs. Microsoft SQL Server vs. RavenDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonRavenDB  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionLarge scale data warehouse service with append-only tablesA multi-model DBMS and application serverMicrosofts flagship relational DBMSOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSDocument store
Secondary database modelsDocument storeDocument 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
Score60.38
Rank#19  Overall
#13  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websitecloud.google.com/­bigquerywww.intersystems.com/­products/­cachewww.microsoft.com/­en-us/­sql-serverravendb.net
Technical documentationcloud.google.com/­bigquery/­docsdocs.intersystems.comlearn.microsoft.com/­en-US/­sql/­sql-serverravendb.net/­docs
DeveloperGoogleInterSystemsMicrosoftHibernating Rhinos
Initial release2010199719892010
Current release2018.1.4, May 2020SQL Server 2022, November 20225.4, July 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoAGPL version 3, commercial license 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 languageC++C#
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeyesdepending on used data modelyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.noyesyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesyesyesSQL-like query language (RQL)
APIs and other access methodsRESTful HTTP/JSON API.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
.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 languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C#
C++
Java
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayes
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenonetables can be distributed across several files (horizontal partitioning); sharding through federationSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, but depending on the SQL-Server EditionMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate 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 integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACIDACIDACID, 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.noyesyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and rolesfine grained access rights according to SQL-standardAuthorization levels configured per client per database

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More resources
Google BigQueryInterSystems CachéMicrosoft SQL ServerRavenDB
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