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DBMS > Apache Spark (SQL) vs. Kuzu vs. Yaacomo

System Properties Comparison Apache Spark (SQL) vs. Kuzu vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonKuzu  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable property Graph DBMS built for query speed and scalabilityOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.76
Rank#30  Overall
#18  Relational DBMS
Score0.07
Rank#350  Overall
#37  Graph DBMS
Websitespark.apache.org/­sqlkuzudb.comyaacomo.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.kuzudb.com
DeveloperApache Software FoundationQ2WEB GmbH
Initial release201420222009
Current release3.5.0 ( 2.13), September 20230.4.2, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoMIT licensecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++
Server operating systemsLinux
OS X
Windows
server-lessAndroid
Linux
Windows
Data schemeyesyesyes
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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
CLI Client
Cypher Query Language
JDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Python
Rust
Server-side scripts infoStored proceduresnono
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corenonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
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 controlnonofine grained access rights according to SQL-standard

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More resources
Apache Spark (SQL)KuzuYaacomo
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