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DBMS > Google Cloud Datastore vs. HugeGraph vs. Sadas Engine vs. Stardog

System Properties Comparison Google Cloud Datastore vs. HugeGraph vs. Sadas Engine vs. Stardog

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonSadas Engine  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument storeGraph DBMSRelational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
www.sadasengine.comwww.stardog.com
Technical documentationcloud.google.com/­datastore/­docshugegraph.apache.org/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.stardog.com
DeveloperGoogleBaiduSADAS s.r.l.Stardog-Union
Initial release2008201820062010
Current release0.98.07.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree trial version availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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 languageJavaC++Java
Server operating systemshostedLinux
macOS
Unix
AIX
Linux
Windows
Linux
macOS
Windows
Data schemeschema-freeyesyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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 infoImport/export of XML data possible
Secondary indexesyesyes infoalso supports composite index and range indexyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query language (GQL)noyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineasynchronous Gremlin script jobsnouser defined functions and aggregates, HTTP Server extensions in Java
TriggersCallbacks using the Google Apps Enginenonoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBasenoneMulti-source replication in HA-Cluster
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 ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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.noyesyes infomanaged by 'Learn by Usage'yes
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, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
Google Cloud DatastoreHugeGraphSadas EngineStardog
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