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DBMS > Apache Impala vs. Pinecone vs. RDFox

System Properties Comparison Apache Impala vs. Pinecone vs. RDFox

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonPinecone  Xexclude from comparisonRDFox  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA managed, cloud-native vector databaseHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSVector DBMSGraph DBMS
RDF store
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score3.02
Rank#87  Overall
#3  Vector DBMS
Score0.22
Rank#305  Overall
#25  Graph DBMS
#15  RDF stores
Websiteimpala.apache.orgwww.pinecone.iowww.oxfordsemantic.tech
Technical documentationimpala.apache.org/­impala-docs.htmldocs.pinecone.io/­docs/­overviewdocs.oxfordsemantic.tech
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPinecone Systems, IncOxford Semantic Technologies
Initial release201320192017
Current release4.1.0, June 20226.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinuxhostedLinux
macOS
Windows
Data schemeyesyes infoRDF schemas
Typing infopredefined data types such as float or dateyesString, Number, Booleanyes
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
Secondary indexesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIRESTful HTTP API
SPARQL 1.1
Supported programming languagesAll languages supporting JDBC/ODBCPythonC
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduce
Triggersno
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorreplication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRoles, resources, and access types

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More resources
Apache ImpalaPineconeRDFox
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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18 July 2024, Samsung Global Newsroom

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16 July 2024, University of Oxford

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