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DBMS > EsgynDB vs. FeatureBase vs. Spark SQL vs. SQream DB

System Properties Comparison EsgynDB vs. FeatureBase vs. Spark SQL vs. SQream DB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFeatureBase  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  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.Spark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websitewww.esgyn.cnwww.featurebase.comspark.apache.org/­sqlsqream.com
Technical documentationdocs.featurebase.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperEsgynMolecula and Pilosa Open Source ContributorsApache Software FoundationSQream Technologies
Initial release2015201720142017
Current release2022, May 20223.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaGoScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinux
macOS
Linux
OS X
Windows
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Types
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.nonono
Secondary indexesyesnonono
SQL infoSupport of SQLyesSQL queriesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
.Net
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
Python
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnouser defined functions in Python
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyesnonenone
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 dataACIDyesnoACID
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardno

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More resources
EsgynDBFeatureBaseSpark SQLSQream DB
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