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DBMS > Google Cloud Datastore vs. Heroic vs. HugeGraph vs. Oracle NoSQL

System Properties Comparison Google Cloud Datastore vs. Heroic vs. HugeGraph vs. Oracle NoSQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHeroic  Xexclude from comparisonHugeGraph  Xexclude from comparisonOracle NoSQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA fast-speed and highly-scalable Graph DBMSA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelDocument storeTime Series DBMSGraph DBMSDocument store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­spotify/­heroicgithub.com/­hugegraph
hugegraph.apache.org
www.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationcloud.google.com/­datastore/­docsspotify.github.io/­heroichugegraph.apache.org/­docsdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperGoogleSpotifyBaiduOracle
Initial release2008201420182011
Current release0.924.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemshostedLinux
macOS
Unix
Linux
Solaris SPARC/x86
Data schemeschema-freeschema-freeyesSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or dateyes, details hereyesyesoptional
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 infovia Elasticsearchyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
C
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App Enginenoasynchronous Gremlin script jobsno
TriggersCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesyes infodepending on used storage backend, e.g. Cassandra and HBaseElectable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownovia hugegraph-sparkwith Hadoop integration
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
Immediate Consistency
Eventual ConsistencyEventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDconfigurable infoACID within a storage node (=shard)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infooff heap cache
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsAccess rights for users and roles

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More resources
Google Cloud DatastoreHeroicHugeGraphOracle NoSQL
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