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

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

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonPrometheus  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 TrafodionOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Websitewww.esgyn.cnprometheus.iospark.apache.org/­sqlyanza.com
Technical documentationprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynApache Software FoundationYanza
Initial release2015201520142015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open 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++, JavaGoScala
Server operating systemsLinuxLinux
Windows
Linux
OS X
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesNumeric data onlyyesno
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 possiblenono
Secondary indexesyesnonono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIJDBC
ODBC
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
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 nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoby Federationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonono

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More resources
EsgynDBPrometheusSpark SQLYanza
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