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DBMS > Amazon SimpleDB vs. Databricks vs. FatDB vs. PlanetScale

System Properties Comparison Amazon SimpleDB vs. Databricks vs. FatDB vs. PlanetScale

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonPlanetScale  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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 ScioreThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Scalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelKey-value storeDocument store
Relational DBMS
Document store
Key-value store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.databricks.complanetscale.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.databricks.complanetscale.com/­docs
DeveloperAmazonDatabricksFatCloudPlanetScale
Initial release2007201320122020
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Go
Server operating systemshostedhostedWindowsDocker
Linux
macOS
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or datenoyesyes
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.yes
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnowith Databricks SQLno infoVia inetgration in SQL Serveryes infowith proprietary extensions
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Python
R
Scala
C#Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infovia applicationsyes infoproprietary syntax
Triggersnoyes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesselectable replication factorMulti-source replication
Source-replica replication
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 ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no infoCan implement custom security layer via applicationsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Amazon SimpleDBDatabricksFatDBPlanetScale
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon SimpleDBDatabricksFatDBPlanetScale
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