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DBMS > Kinetica vs. Qdrant vs. Spark SQL vs. STSdb

System Properties Comparison Kinetica vs. Qdrant vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonQdrant  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA high-performance vector database with neural network or semantic-based matchingSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSVector DBMSRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.kinetica.comgithub.com/­qdrant/­qdrant
qdrant.tech
spark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.kinetica.comqdrant.tech/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaQdrantApache Software FoundationSTS Soft SC
Initial release2012202120142011
Current release7.1, August 20213.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++RustScalaC#
Server operating systemsLinuxDocker
Linux
macOS
Windows
Linux
OS X
Windows
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanyesyes infoprimitive types and user defined types (classes)
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 indexesyesyes infoKeywords, numberic ranges, geo, full-textnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
.NET Client API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationCollection-level replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency, tunable consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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 RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelKey-based authenticationnono

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More resources
KineticaQdrantSpark SQLSTSdb
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