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DBMS > Kinetica vs. Spark SQL vs. TigerGraph vs. WakandaDB

System Properties Comparison Kinetica vs. Spark SQL vs. TigerGraph vs. WakandaDB

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSRelational DBMSGraph DBMSObject oriented DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.kinetica.comspark.apache.org/­sqlwww.tigergraph.comwakanda.github.io
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.comwakanda.github.io/­doc
DeveloperKineticaApache Software FoundationWakanda SAS
Initial release2012201420172012
Current release7.1, August 20213.5.0 ( 2.13), September 20232.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ScalaC++C++, JavaScript
Server operating systemsLinuxLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyesyes
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 indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsSQL-like query language (GSQL)no
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
JavaScript
Server-side scripts infoStored proceduresuser defined functionsnoyesyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yes infoGPU vRAM or System RAMnonono
User concepts infoAccess controlAccess rights for users and roles on table levelnoRole-based access controlyes

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More resources
KineticaSpark SQLTigerGraphWakandaDB
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