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DBMS > Google Cloud Datastore vs. HugeGraph vs. Microsoft Azure AI Search vs. ObjectBox vs. Sphinx

System Properties Comparison Google Cloud Datastore vs. HugeGraph vs. Microsoft Azure AI Search vs. ObjectBox vs. Sphinx

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentExtremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeGraph DBMSSearch engineObject oriented DBMSSearch engine
Secondary database modelsVector DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchobjectbox.iosphinxsearch.com
Technical documentationcloud.google.com/­datastore/­docshugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.objectbox.iosphinxsearch.com/­docs
DeveloperGoogleBaiduMicrosoftObjectBox LimitedSphinx Technologies Inc.
Initial release20082018201520172001
Current release0.9V13.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C++
Server operating systemshostedLinux
macOS
Unix
hostedAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyesno
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.nononono
Secondary indexesyesyes infoalso supports composite index and range indexyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language (GQL)nononoSQL-like query language (SphinxQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary native APIProprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C#
Java
JavaScript
Python
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresusing Google App Engineasynchronous Gremlin script jobsnonono
TriggersCallbacks using the Google Apps Enginenononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding 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 infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud serviceonline/offline synchronization between client and servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowvia hugegraph-sparknonono
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.Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsyes infousing Azure authenticationyesno
More information provided by the system vendor
Google Cloud DatastoreHugeGraphMicrosoft Azure AI SearchObjectBoxSphinx
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More resources
Google Cloud DatastoreHugeGraphMicrosoft Azure AI SearchObjectBoxSphinx
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