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DBMS > Google BigQuery vs. HarperDB vs. LeanXcale vs. Microsoft SQL Server

System Properties Comparison Google BigQuery vs. HarperDB vs. LeanXcale vs. Microsoft SQL Server

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonHarperDB  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesMicrosofts flagship relational DBMS
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score52.67
Rank#19  Overall
#13  Relational DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Score0.28
Rank#286  Overall
#41  Key-value stores
#130  Relational DBMS
Score807.76
Rank#3  Overall
#3  Relational DBMS
Websitecloud.google.com/­bigquerywww.harperdb.iowww.leanxcale.comwww.microsoft.com/­en-us/­sql-server
Technical documentationcloud.google.com/­bigquery/­docsdocs.harperdb.io/­docslearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperGoogleHarperDBLeanXcaleMicrosoft
Initial release2010201720151989
Current release3.1, August 2021SQL Server 2022, November 2022
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availablecommercialcommercial 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 languageNode.jsC++
Server operating systemshostedLinux
OS X
Linux
Windows
Data schemeyesdynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data 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.nonoyes
Secondary indexesnoyesyes
SQL infoSupport of SQLyesSQL-like data manipulation statementsyes infothrough Apache Derbyyes
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C
Java
Scala
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptCustom Functions infosince release 3.1Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneA table resides as a whole on one (or more) nodes in a clustertables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesyes infothe nodes on which a table resides can be definedyes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataAtomic execution of specific operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Google BigQueryHarperDBLeanXcaleMicrosoft SQL Server
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