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DBMS > HugeGraph vs. Oracle Berkeley DB vs. SQLite vs. Stardog

System Properties Comparison HugeGraph vs. Oracle Berkeley DB vs. SQLite vs. Stardog

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSQLite  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSWidely used in-process key-value storeWidely used embeddable, in-process RDBMSEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelGraph DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#340  Overall
#31  Graph DBMS
Score2.80
Rank#112  Overall
#20  Key-value stores
#3  Native XML DBMS
Score118.16
Rank#10  Overall
#7  Relational DBMS
Score2.03
Rank#136  Overall
#12  Graph DBMS
#6  RDF stores
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.sqlite.orgwww.stardog.com
Technical documentationhugegraph.apache.org/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.sqlite.org/­docs.htmldocs.stardog.com
DeveloperBaiduOracle infooriginally developed by Sleepycat, which was acquired by OracleDwayne Richard HippStardog-Union
Initial release2018199420002010
Current release0.918.1.40, May 20203.45.2  (12 March 2024), March 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infocommercial license availableOpen Source infoPublic Domaincommercial 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)CJava
Server operating systemsLinux
macOS
Unix
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
server-lessLinux
macOS
Windows
Data schemeyesschema-freeyes infodynamic column typesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesnoyes infonot rigid because of 'dynamic typing' concept.yes
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.noyes infoonly with the Berkeley DB XML editionnono infoImport/export of XML data possible
Secondary indexesyes infoalso supports composite index and range indexyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoyes infoSQL interfaced based on SQLite is availableyes infoSQL-92 is not fully supportedYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
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 infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnonouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infoonly for the SQL APIyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasenonenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoedges in graphnoyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infovia file-system locksyes
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.yesyesyesyes
User concepts infoAccess controlUsers, roles and permissionsnonoAccess rights for users and roles

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More resources
HugeGraphOracle Berkeley DBSQLiteStardog
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