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DBMS > Google Cloud Datastore vs. HugeGraph vs. LevelDB vs. Microsoft Access vs. ToroDB

System Properties Comparison Google Cloud Datastore vs. HugeGraph vs. LevelDB vs. Microsoft Access vs. ToroDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMicrosoft 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.)A MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelDocument storeGraph DBMSKey-value storeRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score0.15
Rank#339  Overall
#33  Graph DBMS
Score2.75
Rank#107  Overall
#19  Key-value stores
Score105.40
Rank#11  Overall
#8  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
github.com/­google/­leveldbwww.microsoft.com/­en-us/­microsoft-365/­accessgithub.com/­torodb/­server
Technical documentationcloud.google.com/­datastore/­docshugegraph.apache.org/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddeveloper.microsoft.com/­en-us/­access
DeveloperGoogleBaiduGoogleMicrosoft8Kdata
Initial release20082018201119922016
Current release0.91.23, February 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoBSDcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++Java
Server operating systemshostedLinux
macOS
Unix
Illumos
Linux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsAll OS with a Java 7 VM
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesnoyesyes infostring, integer, double, boolean, date, object_id
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 indexnoyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoyes infobut not compliant to any SQL standard
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
DAO
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresusing Google App Engineasynchronous Gremlin script jobsnoyes infosince Access 2010 using the ACE-engine
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
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBasenonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowvia hugegraph-sparknono
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 ConsistencyEventual Consistency
Immediate 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 TransactionsACIDnoACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes 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.noyes
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 2003Access rights for users and roles

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More resources
Google Cloud DatastoreHugeGraphLevelDBMicrosoft AccessToroDB
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