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DBMS > GigaSpaces vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. Splunk

System Properties Comparison GigaSpaces vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. Splunk

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSplunk  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSearch-as-a-service for web and mobile app developmentAnalytics Platform for Big Data
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Document storeSearch engineSearch engine
Secondary database modelsGraph DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score5.52
Rank#59  Overall
#6  Search engines
Score89.10
Rank#14  Overall
#2  Search engines
Websitewww.gigaspaces.comcloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­searchwww.splunk.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­datastore/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.splunk.com/­Documentation/­Splunk
DeveloperGigaspaces TechnologiesGoogleMicrosoftSplunk Inc.
Initial release2000200820152003
Current release15.5, September 2020V1
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercialcommercial infoLimited free edition and free developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net
Server operating systemsLinux
macOS
Solaris
Windows
hostedhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.no infoXML can be used for describing objects metadatanonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like query language (GQL)nono infoSplunk Search Processing Language for search commands
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP REST
Supported programming languages.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Python
C#
Java
JavaScript
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesusing Google App Enginenoyes
Triggersyes, event driven architectureCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication using Paxosyes infoImplicit feature of the cloud serviceMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate 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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching
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.yesnonono
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationAccess rights for users and roles

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More resources
GigaSpacesGoogle Cloud DatastoreMicrosoft Azure AI SearchSplunk
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