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DBMS > EsgynDB vs. Prometheus vs. Spark SQL vs. Splice Machine

System Properties Comparison EsgynDB vs. Prometheus vs. Spark SQL vs. Splice Machine

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
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 processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational 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
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.esgyn.cnprometheus.iospark.apache.org/­sqlsplicemachine.com
Technical documentationprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperEsgynApache Software FoundationSplice Machine
Initial release2015201520142014
Current release3.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaGoScalaJava
Server operating systemsLinuxLinux
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlyyesyes
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 possibleno
Secondary indexesyesnonoyes
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnonoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoby FederationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoAccess rights for users, groups and roles according to SQL-standard

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EsgynDBPrometheusSpark SQLSplice Machine
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