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

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

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonInfobright  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh 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 processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cnignitetech.com/­softwarelibrary/­infobrightdbspark.apache.org/­sqlyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynIgnite Technologies Inc.; formerly InfoBright Inc.Apache Software FoundationYanza
Initial release2015200520142015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaCScala
Server operating systemsLinuxLinux
Windows
Linux
OS X
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesno infoKnowledge Grid Technology used insteadnono
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
JDBC
ODBC
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersnononoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesnono

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More resources
EsgynDBInfobrightSpark SQLYanza
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