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DBMS > Brytlyt vs. Citus vs. Databricks vs. Kinetica

System Properties Comparison Brytlyt vs. Citus vs. Databricks vs. Kinetica

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe 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 CPUs
Primary database modelRelational DBMSRelational DBMSDocument store
Relational DBMS
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitebrytlyt.iowww.citusdata.comwww.databricks.comwww.kinetica.com
Technical documentationdocs.brytlyt.iodocs.citusdata.comdocs.databricks.comdocs.kinetica.com
DeveloperBrytlytDatabricksKinetica
Initial release2016201020132012
Current release5.0, August 20238.1, December 20187.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDACC, C++
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes
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.yes infospecific XML-type available, but no XML query functionality.yes infospecific XML type available, but no XML query functionalityyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyes infostandard, with numerous extensionswith Databricks SQLSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregatesuser defined functions
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles on table level
More information provided by the system vendor
BrytlytCitusDatabricksKinetica
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
BrytlytCitusDatabricksKinetica
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Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

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London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
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