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DBMS > EJDB vs. Kinetica vs. Spark SQL

System Properties Comparison EJDB vs. Kinetica vs. Spark SQL

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Fully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.kinetica.comspark.apache.org/­sql
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftmotionsKineticaApache Software Foundation
Initial release201220122014
Current release7.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC, C++Scala
Server operating systemsserver-lessLinuxLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyes
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.nono
Secondary indexesnoyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsin-process shared libraryJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyes
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.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users and roles on table levelno

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More resources
EJDBKineticaSpark SQL
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