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DBMS > Amazon SimpleDB vs. EsgynDB vs. Prometheus vs. Spark SQL

System Properties Comparison Amazon SimpleDB vs. EsgynDB vs. Prometheus vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreEnterprise-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 processing
Primary database modelKey-value storeRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#139  Overall
#24  Key-value stores
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score7.92
Rank#51  Overall
#2  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.esgyn.cnprometheus.iospark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­simpledbprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonEsgynApache Software Foundation
Initial release2007201520152014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaGoScala
Server operating systemshostedLinuxLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesNumeric data onlyyes
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 indexesyes infoAll columns are indexed automaticallyyesnono
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistencynone
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnono
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 controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardnono

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More resources
Amazon SimpleDBEsgynDBPrometheusSpark SQL
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Amazon SimpleDB Management in Eclipse | AWS News Blog
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