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DBMS > Amazon SimpleDB vs. Apache Impala vs. GeoSpock vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. GeoSpock vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  Xexclude from comparisonGeoSpock  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded 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 ScioreAnalytic DBMS for HadoopSpatial and temporal data processing engine for extreme data scaleFully managed big data interactive analytics platform
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeTime Series DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteaws.amazon.com/­simpledbimpala.apache.orggeospock.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaGeoSpockMicrosoft
Initial release200720132019
Current release4.1.0, June 20222.0, September 2019cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, Javascript
Server operating systemshostedLinuxhostedhosted
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonoyes
Secondary indexesyes infoAll columns are indexed automaticallyyestemporal, categoricalall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like DML and DDL statementsANSI SQL for query only (using Presto)Kusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoYes, possible languages: KQL, Python, R
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingAutomatic shardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate 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 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.nonono
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 roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per tableAzure Active Directory Authentication

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More resources
Amazon SimpleDBApache ImpalaGeoSpockMicrosoft Azure Data Explorer
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Amazon SimpleDB Management in Eclipse | AWS News Blog
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