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DBMS > Google BigQuery vs. Hazelcast vs. Microsoft SQL Server vs. NCache

System Properties Comparison Google BigQuery vs. Hazelcast vs. Microsoft SQL Server vs. NCache

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonNCache  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesA widely adopted in-memory data gridMicrosofts flagship relational DBMSOpen-Source and Enterprise in-memory Key-Value Store
Primary database modelRelational DBMSKey-value storeRelational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Graph DBMS
Spatial DBMS
Document store
Search engine infoUsing distributed Lucene
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score52.67
Rank#19  Overall
#13  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score807.76
Rank#3  Overall
#3  Relational DBMS
Score0.91
Rank#196  Overall
#29  Key-value stores
Websitecloud.google.com/­bigqueryhazelcast.comwww.microsoft.com/­en-us/­sql-serverwww.alachisoft.com/­ncache
Technical documentationcloud.google.com/­bigquery/­docshazelcast.org/­imdg/­docslearn.microsoft.com/­en-US/­sql/­sql-serverwww.alachisoft.com/­resources/­docs
DeveloperGoogleHazelcastMicrosoftAlachisoft
Initial release2010200819892005
Current release5.3.6, November 2023SQL Server 2022, November 20225.3.3, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial inforestricted free version is availableOpen Source infoEnterprise Edition 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 languageJavaC++C#, .NET, .NET Core, Java
Server operating systemshostedAll OS with a Java VMLinux
Windows
Linux
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counter
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 infothe object must implement a serialization strategyyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesSQL-like query languageyesSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.
APIs and other access methodsRESTful HTTP/JSON APIJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
IDistributedCache
JCache
LINQ
Proprietary native API
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infoEvent Listeners, Executor ServicesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano infosupport for stored procedures with SQL-Server CLR
Triggersnoyes infoEventsyesyes infoNotifications
Partitioning methods infoMethods for storing different data on different nodesnoneShardingtables can be distributed across several files (horizontal partitioning); sharding through federationyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes, but depending on the SQL-Server Editionyes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataone or two-phase-commit; repeatable reads; read commitedACIDoptimistic locking and pessimistic locking
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.noyesyesyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)
More information provided by the system vendor
Google BigQueryHazelcastMicrosoft SQL ServerNCache
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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More resources
Google BigQueryHazelcastMicrosoft SQL ServerNCache
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