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DBMS > Amazon SimpleDB vs. Quasardb vs. Spark SQL vs. Sqrrl

System Properties Comparison Amazon SimpleDB vs. Quasardb vs. Spark SQL vs. Sqrrl

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreDistributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processingAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeTime Series DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbquasar.aispark.apache.org/­sqlsqrrl.com
Technical documentationdocs.aws.amazon.com/­simpledbdoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonquasardbApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2007200920142012
Current release3.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaJava
Server operating systemshostedBSD
Linux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes infointeger and binaryyesyes
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
Secondary indexesyes infoAll columns are indexed automaticallyyes infowith tagsnoyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIHTTP APIJDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnononono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infoconsistent hashingyes, utilizing Spark CoreSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with selectable replication factornoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTransient modeno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Cryptographically strong user authentication and audit trailnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon SimpleDBQuasardbSpark SQLSqrrl
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