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DBMS > atoti vs. Google Cloud Datastore vs. Realm vs. searchxml vs. Sphinx

System Properties Comparison atoti vs. Google Cloud Datastore vs. Realm vs. searchxml vs. Sphinx

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRealm  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 PlatformA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataDBMS 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 storeDocument storeNative XML DBMS
Search engine
Search engine
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
Score7.41
Rank#52  Overall
#8  Document stores
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websiteatoti.iocloud.google.com/­datastorerealm.iowww.searchxml.net/­category/­productssphinxsearch.com
Technical documentationdocs.atoti.iocloud.google.com/­datastore/­docsrealm.io/­docswww.searchxml.net/­support/­handoutssphinxsearch.com/­docs
DeveloperActiveViamGoogleRealm, acquired by MongoDB in May 2019informationpartners gmbhSphinx Technologies Inc.
Initial release2008201420152001
Current release1.03.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen SourcecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemshostedAndroid
Backend: server-less
iOS
Windows
WindowsFreeBSD
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 API
WebDAV
XQuery
XSLT
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
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 Engineno inforuns within the applications so server-side scripts are unnecessaryyes infoon the application serverno
TriggersCallbacks using the Google Apps Engineyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingnonenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneyes 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 TransactionsACIDmultiple readers, single writerno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
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.yesnoyes infoIn-Memory realmno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesDomain, group and role-based access control at the document level and for application servicesno

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More resources
atotiGoogle Cloud DatastoreRealmsearchxmlSphinx
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