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DBMS > HugeGraph vs. OrigoDB vs. RavenDB vs. Spark SQL vs. Stardog

System Properties Comparison HugeGraph vs. OrigoDB vs. RavenDB vs. Spark SQL vs. Stardog

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonOrigoDB  Xexclude from comparisonRavenDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSA fully ACID in-memory object graph databaseOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelGraph DBMSDocument store
Object oriented DBMS
Document storeRelational DBMSGraph DBMS
RDF store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitegithub.com/­hugegraph
hugegraph.apache.org
origodb.comravendb.netspark.apache.org/­sqlwww.stardog.com
Technical documentationhugegraph.apache.org/­docsorigodb.com/­docsravendb.net/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperBaiduRobert Friberg et alHibernating RhinosApache Software FoundationStardog-Union
Initial release20182009 infounder the name LiveDB201020142010
Current release0.95.4, July 20223.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0commercial 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 servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C#ScalaJava
Server operating systemsLinux
macOS
Unix
Linux
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyesyesschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsnoyesyes
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 infocan be achieved using .NETnono infoImport/export of XML data possible
Secondary indexesyes infoalso supports composite index and range indexyesyesnoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnonoSQL-like query language (RQL)SQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
HTTP API
LINQ
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
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 languagesGroovy
Java
Python
.Net.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyesyesnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infoDomain Eventsyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning infoclient side managed; servers are not synchronizedShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationMulti-source replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoedges in graphdepending on modelnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID, Cluster-wide transaction availablenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlUsers, roles and permissionsRole based authorizationAuthorization levels configured per client per databasenoAccess rights for users and roles

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More resources
HugeGraphOrigoDBRavenDBSpark SQLStardog
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