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DBMS > EsgynDB vs. Firebolt vs. Postgres-XL vs. Spark SQL

System Properties Comparison EsgynDB vs. Firebolt vs. Postgres-XL vs. Spark SQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFirebolt  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cnwww.firebolt.iowww.postgres-xl.orgspark.apache.org/­sql
Technical documentationdocs.firebolt.iowww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynFirebolt Analytics Inc.Apache Software Foundation
Initial release201520202014 infosince 2012, originally named StormDB2014
Current release10 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaCScala
Server operating systemsLinuxhostedLinux
macOS
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyesyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetGo
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnouser defined functionsno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersdepending on storage layernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
EsgynDBFireboltPostgres-XLSpark SQL
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