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DBMS > Apache Impala vs. Datomic vs. GraphDB vs. HugeGraph

System Properties Comparison Apache Impala vs. Datomic vs. GraphDB vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEnterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.A fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSRelational DBMSGraph DBMS
RDF store
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.25
Rank#91  Overall
#7  Graph DBMS
#4  RDF stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteimpala.apache.orgwww.datomic.comwww.ontotext.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comgraphdb.ontotext.com/­documentationhugegraph.apache.org/­docs
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectOntotextBaidu
Initial release2013201220002018
Current release4.1.0, June 20221.0.7075, December 202310.4, October 20230.9
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freecommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureJavaJava
Server operating systemsLinuxAll OS with a Java VMAll OS with a Java VM
Linux
OS X
Windows
Linux
macOS
Unix
Data schemeyesyesschema-free and OWL/RDFS-schema support; RDF shapesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like DML and DDL statementsnostored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCno
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIGeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Groovy
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionswell-defined plugin interfaces; JavaScript server-side extensibilityasynchronous Gremlin script jobs
TriggersnoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersnoneyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Eventual Consistency
Foreign keys infoReferential integritynonoyes infoConstraint checkingyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoDefault Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.Users, roles and permissions
More information provided by the system vendor
Apache ImpalaDatomicGraphDB infoformer name: OWLIMHugeGraph
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
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