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DBMS > Amazon SimpleDB vs. InterSystems Caché vs. Spark SQL vs. Sqrrl

System Properties Comparison Amazon SimpleDB vs. InterSystems Caché vs. Spark SQL vs. Sqrrl

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  Xexclude from comparisonSqrrl  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.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 ScioreA multi-model DBMS and application serverSpark SQL is a component on top of 'Spark Core' for structured data processingAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value storeKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.intersystems.com/­products/­cachespark.apache.org/­sqlsqrrl.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonInterSystemsApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.
Initial release2007199720142012
Current release2018.1.4, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
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 languageScalaJava
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freedepending on used data modelyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes
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.yesno
Secondary indexesyes infoAll columns are indexed automaticallyyesnoyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP API.NET Client API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C#
C++
Java
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 proceduresnoyesnono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationnoneyes, utilizing Spark CoreSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
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 integritynoyesnono
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 persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and rolesnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon SimpleDBInterSystems CachéSpark SQLSqrrl
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