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

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

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonPrometheus  Xexclude from comparisonQuasardb  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 systemDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMSTime Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.esgyn.cnprometheus.ioquasar.aispark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­simpledbprometheus.io/­docsdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonEsgynquasardbApache Software Foundation
Initial release20072015201520092014
Current release3.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaGoC++Scala
Server operating systemshostedLinuxLinux
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or datenoyesNumeric data onlyyes infointeger and binaryyes
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 indexesyes infoAll columns are indexed automaticallyyesnoyes infowith tagsno
SQL infoSupport of SQLnoyesnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIHTTP 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
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresnonono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyes infoby FederationSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTransient modeno
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-standardnoCryptographically strong user authentication and audit trailno

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More resources
Amazon SimpleDBEsgynDBPrometheusQuasardbSpark SQL
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