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DBMS > EJDB vs. EsgynDB vs. Prometheus vs. Spark SQL

System Properties Comparison EJDB vs. EsgynDB vs. Prometheus vs. Spark SQL

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonPrometheus  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 TrafodionOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational 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
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbwww.esgyn.cnprometheus.iospark.apache.org/­sql
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSoftmotionsEsgynApache Software Foundation
Initial release2012201520152014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++, JavaGoScala
Server operating systemsserver-lessLinuxLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesNumeric data onlyyes
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 infoImport of XML data possibleno
Secondary indexesnoyesnono
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsin-process shared libraryADO.NET
JDBC
ODBC
RESTful HTTP/JSON 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.Net.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencynone
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-standardnono

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More resources
EJDBEsgynDBPrometheusSpark SQL
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