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DBMS > atoti vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. searchxml vs. Sphinx

System Properties Comparison atoti vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. searchxml vs. Sphinx

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonsearchxml  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSearch-as-a-service for web and mobile app developmentDBMS for structured and unstructured content wrapped with an application serverOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelObject oriented DBMSDocument storeSearch engineNative XML DBMS
Search engine
Search engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score5.52
Rank#59  Overall
#6  Search engines
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websiteatoti.iocloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­searchwww.searchxml.net/­category/­productssphinxsearch.com
Technical documentationdocs.atoti.iocloud.google.com/­datastore/­docslearn.microsoft.com/­en-us/­azure/­searchwww.searchxml.net/­support/­handoutssphinxsearch.com/­docs
DeveloperActiveViamGoogleMicrosoftinformationpartners gmbhSphinx Technologies Inc.
Initial release2008201520152001
Current releaseV11.03.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemshostedhostedWindowsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyesno
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 indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like query language (GQL)nonoSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIRESTful HTTP API
WebDAV
XQuery
XSLT
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
JavaScript
Python
C++ infomost other programming languages supported via APIsC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresPythonusing Google App Enginenoyes infoon the application serverno
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingSharding infoImplicit feature of the cloud servicenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoImplicit feature of the cloud serviceyes infosychronisation to multiple collectionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnomultiple readers, single writerno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationDomain, group and role-based access control at the document level and for application servicesno

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More resources
atotiGoogle Cloud DatastoreMicrosoft Azure AI SearchsearchxmlSphinx
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