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DBMS > Google Cloud Datastore vs. GridGain vs. Hazelcast vs. Microsoft SQL Server

System Properties Comparison Google Cloud Datastore vs. GridGain vs. Hazelcast vs. Microsoft SQL Server

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteA widely adopted in-memory data gridMicrosofts flagship relational DBMS
Primary database modelDocument storeKey-value store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score821.56
Rank#3  Overall
#3  Relational DBMS
Websitecloud.google.com/­datastorewww.gridgain.comhazelcast.comwww.microsoft.com/­en-us/­sql-server
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmlhazelcast.org/­imdg/­docslearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperGoogleGridGain Systems, Inc.HazelcastMicrosoft
Initial release2008200720081989
Current releaseGridGain 8.5.15.3.6, November 2023SQL Server 2022, November 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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 languageJava, C++, .NetJavaC++
Server operating systemshostedLinux
OS X
Solaris
Windows
All OS with a Java VMLinux
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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 infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLSQL-like query languageyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.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
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)yes infoEvent Listeners, Executor ServicesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingtables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)yes infoReplicated Mapyes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDone or two-phase-commit; repeatable reads; read commitedACID
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 rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsRole-based access controlfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreGridGainHazelcastMicrosoft SQL Server
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