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DBMS > Apache Spark (SQL) vs. RDFox vs. YugabyteDB

System Properties Comparison Apache Spark (SQL) vs. RDFox vs. YugabyteDB

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonRDFox  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingHigh performance knowledge graph and semantic reasoning engineHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsRelational DBMSDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score0.24
Rank#299  Overall
#24  Graph DBMS
#12  RDF stores
Score2.20
Rank#108  Overall
#53  Relational DBMS
Websitespark.apache.org/­sqlwww.oxfordsemantic.techwww.yugabyte.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oxfordsemantic.techdocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperApache Software FoundationOxford Semantic TechnologiesYugabyte Inc.
Initial release201420172017
Current release3.5.0 ( 2.13), September 20236.0, Septermber 20222024.2, December 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C and C++
Server operating systemsLinux
OS X
Windows
Linux
macOS
Windows
Linux
OS X
Data schemeyesyes infoRDF schemasdepending on used data model
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes, PostgreSQL compatible
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
SPARQL 1.1
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesJava
Python
R
Scala
C
Java
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoyes infosql, plpgsql, C
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonereplication via a shared file systemBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsStrong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnoRoles, resources, and access typesyes

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More resources
Apache Spark (SQL)RDFoxYugabyteDB
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