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DBMS > Amazon SimpleDB vs. Apache Druid vs. IBM Db2 Event Store vs. Spark SQL

System Properties Comparison Amazon SimpleDB vs. Apache Druid vs. IBM Db2 Event Store vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Druid  Xexclude from comparisonIBM Db2 Event Store  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 ScioreOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed Event Store optimized for Internet of Things use casesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeRelational DBMS
Time Series DBMS
Event Store
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbdruid.apache.orgwww.ibm.com/­products/­db2-event-storespark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­simpledbdruid.apache.org/­docs/­latest/­designwww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonApache Software Foundation and contributorsIBMApache Software Foundation
Initial release2007201220172014
Current release29.0.1, April 20242.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercial infofree developer edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Scala
Server operating systemshostedLinux
OS X
Unix
Linux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesyes
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.nonono
Secondary indexesyes infoAll columns are indexed automaticallyyesnono
SQL infoSupport of SQLnoSQL for queryingyes infothrough the embedded Spark runtimeSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
RESTful HTTP/JSON API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyesno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infomanual/auto, time-basedShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, via HDFS, S3 or other storage enginesActive-active shard replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyEventual Consistency
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 applicationnonono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardno

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More resources
Amazon SimpleDBApache DruidIBM Db2 Event StoreSpark SQL
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