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DBMS > Google Cloud Datastore vs. HugeGraph

System Properties Comparison Google Cloud Datastore vs. HugeGraph

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Our visitors often compare Google Cloud Datastore and HugeGraph with Neo4j, Redis and SQLite.

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMS
Primary database modelDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.29
Rank#76  Overall
#13  Document stores
Score0.09
Rank#353  Overall
#33  Graph DBMS
Websitecloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
Technical documentationcloud.google.com/­datastore/­docshugegraph.apache.org/­docs
DeveloperGoogleBaidu
Initial release20082018
Current release0.9
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedLinux
macOS
Unix
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyes
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.nono
Secondary indexesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like query language (GQL)no
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
Server-side scripts infoStored proceduresusing Google App Engineasynchronous Gremlin script jobs
TriggersCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowvia hugegraph-spark
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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
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 permissions

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More resources
Google Cloud DatastoreHugeGraph
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