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DBMS > Amazon DocumentDB vs. Google Cloud Datastore vs. HugeGraph vs. Microsoft Access

System Properties Comparison Amazon DocumentDB vs. Google Cloud Datastore vs. HugeGraph vs. Microsoft Access

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSMicrosoft 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.)
Primary database modelDocument storeDocument storeGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
www.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docshugegraph.apache.org/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperGoogleBaiduMicrosoft
Initial release2019200820181992
Current release0.91902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedhostedLinux
macOS
Unix
Windows infoNot a real database server, but making use of DLLs
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.nonono
Secondary indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noyes infobut not compliant to any SQL standard
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresnousing Google App Engineasynchronous Gremlin script jobsyes infosince Access 2010 using the ACE-engine
TriggersnoCallbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infousing Google Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsno infoa simple user-level security was built in till version Access 2003

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More resources
Amazon DocumentDBGoogle Cloud DatastoreHugeGraphMicrosoft Access
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