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DBMS > Google Cloud Datastore vs. HugeGraph vs. InfinityDB vs. Microsoft Access vs. Microsoft Azure AI Search

System Properties Comparison Google Cloud Datastore vs. HugeGraph vs. InfinityDB vs. Microsoft Access vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSA Java embedded Key-Value Store which extends the Java Map interfaceMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Search-as-a-service for web and mobile app development
Primary database modelDocument storeGraph DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websitecloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
boilerbay.comwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­search
Technical documentationcloud.google.com/­datastore/­docshugegraph.apache.org/­docsboilerbay.com/­infinitydb/­manualdeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-us/­azure/­search
DeveloperGoogleBaiduBoiler Bay Inc.MicrosoftMicrosoft
Initial release20082018200219922015
Current release0.94.01902 (16.0.11328.20222), March 2019V1
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++
Server operating systemshostedLinux
macOS
Unix
All OS with a Java VMWindows infoNot a real database server, but making use of DLLshosted
Data schemeschema-freeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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 indexno infomanual creation possible, using inversions based on multi-value capabilityyesyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoyes infobut not compliant to any SQL standardno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
JavaC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresusing Google App Engineasynchronous Gremlin script jobsnoyes infosince Access 2010 using the ACE-engineno
TriggersCallbacks using the Google Apps Enginenonoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenonenoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBasenonenoneyes infoImplicit feature of the cloud service
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 Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphno infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
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 permissionsnono infoa simple user-level security was built in till version Access 2003yes infousing Azure authentication

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More resources
Google Cloud DatastoreHugeGraphInfinityDBMicrosoft AccessMicrosoft Azure AI Search
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