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DBMS > EsgynDB vs. FeatureBase vs. Infobright vs. Spark SQL

System Properties Comparison EsgynDB vs. FeatureBase vs. Infobright vs. Spark SQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFeatureBase  Xexclude from comparisonInfobright  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cnwww.featurebase.comignitetech.com/­softwarelibrary/­infobrightdbspark.apache.org/­sql
Technical documentationdocs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynMolecula and Pilosa Open Source ContributorsIgnite Technologies Inc.; formerly InfoBright Inc.Apache Software Foundation
Initial release2015201720052014
Current release2022, May 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open 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 languageC++, JavaGoCScala
Server operating systemsLinuxLinux
macOS
Linux
Windows
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.nononono
Secondary indexesyesnono infoKnowledge Grid Technology used insteadno
SQL infoSupport of SQLyesSQL queriesyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
JDBC
Kafka Connector
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Python
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesSource-replica replicationnone
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 integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesno

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EsgynDBFeatureBaseInfobrightSpark SQL
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