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DBMS > Amazon Aurora vs. Cloudflare Workers KV vs. Netezza vs. Sadas Engine vs. Spark SQL

System Properties Comparison Amazon Aurora vs. Cloudflare Workers KV vs. Netezza vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Data warehouse and analytics appliance part of IBM PureSystemsSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score0.32
Rank#283  Overall
#40  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.cloudflare.com/­developer-platform/­workers-kvwww.ibm.com/­products/­netezzawww.sadasengine.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldevelopers.cloudflare.com/­kv/­apiwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonCloudflareIBMSADAS s.r.l.Apache Software Foundation
Initial release20152018200020062014
Current release8.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Scala
Server operating systemshostedhostedLinux infoincluded in applianceAIX
Linux
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.yesnonono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLyesnoyesyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
HTTP REST
Proprietary protocol
JDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyesnono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standardno

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More resources
Amazon AuroraCloudflare Workers KVNetezza infoAlso called PureData System for Analytics by IBMSadas EngineSpark SQL
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