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DBMS > Databricks vs. Kinetica vs. SwayDB vs. TigerGraph

System Properties Comparison Databricks vs. Kinetica vs. SwayDB vs. TigerGraph

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonSwayDB  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Fully vectorized database across both GPUs and CPUsAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storageA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeGraph DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websitewww.databricks.comwww.kinetica.comswaydb.simer.auwww.tigergraph.com
Technical documentationdocs.databricks.comdocs.kinetica.comdocs.tigergraph.com
DeveloperDatabricksKineticaSimer Plaha
Initial release2013201220182017
Current release7.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU Affero GPL V3.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ScalaC++
Server operating systemshostedLinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.yesnonono
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsnoSQL-like query language (GSQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Kotlin
Scala
C++
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnoyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 dataACIDnoAtomic execution of operationsACID
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.noyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelnoRole-based access control
More information provided by the system vendor
DatabricksKineticaSwayDBTigerGraph
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksKineticaSwayDBTigerGraph
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