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DBMS > EJDB vs. EsgynDB vs. Microsoft Azure AI Search vs. Spark SQL

System Properties Comparison EJDB vs. EsgynDB vs. Microsoft Azure AI Search vs. Spark SQL

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSearch-as-a-service for web and mobile app developmentSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSSearch engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.esgyn.cnazure.microsoft.com/­en-us/­services/­searchspark.apache.org/­sql
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdlearn.microsoft.com/­en-us/­azure/­searchspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftmotionsEsgynMicrosoftApache Software Foundation
Initial release2012201520152014
Current releaseV13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++, JavaScala
Server operating systemsserver-lessLinuxhostedLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsin-process shared libraryADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
Java
JavaScript
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
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.nonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardyes infousing Azure authenticationno

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More resources
EJDBEsgynDBMicrosoft Azure AI SearchSpark SQL
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