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DBMS > EJDB vs. HBase vs. Spark SQL

System Properties Comparison EJDB vs. HBase vs. Spark SQL

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Wide-column store based on Apache Hadoop and on concepts of BigTableSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#294  Overall
#44  Document stores
Score31.25
Rank#26  Overall
#2  Wide column stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbhbase.apache.orgspark.apache.org/­sql
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftmotionsApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release201220082014
Current release2.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoApache version 2Open 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 languageCJavaScala
Server operating systemsserver-lessLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idoptions to bring your own types, AVROyes
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 indexesnonono
SQL infoSupport of SQLnonoSQL-like DML and DDL statements
APIs and other access methodsin-process shared libraryJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)no
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.yesno
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno

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More resources
EJDBHBaseSpark SQL
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