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DBMS > Amazon Aurora vs. Apache Impala vs. Google Cloud Datastore vs. RDF4J vs. SAP Adaptive Server

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Google Cloud Datastore vs. RDF4J vs. SAP Adaptive Server

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSAP Adaptive Server infoformer name: Sybase ASE  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS
Primary database modelRelational DBMSRelational DBMSDocument storeRDF storeRelational DBMS
Secondary database modelsDocument storeDocument storeSpatial DBMS infowith Boeing's Spatial Query Server
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score35.09
Rank#25  Overall
#17  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgcloud.google.com/­datastorerdf4j.orgwww.sap.com/­products/­technology-platform/­sybase-ase.html
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docsrdf4j.org/­documentationhelp.sap.com/­docs/­SAP_ASE
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SAP, Sybase
Initial release20152013200820041987
Current release4.1.0, June 202216.0
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC and C++
Server operating systemshostedLinuxhostedLinux
OS X
Unix
Windows
AIX
HP-UX
Linux
Solaris
Unix
Windows
Data schemeyesyesschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (GQL)noyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
All languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C
C++
Cobol
Java
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceusing Google App EngineyesJava and Transact-SQL
TriggersyesnoCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication using PaxosnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Amazon AuroraApache ImpalaGoogle Cloud DatastoreRDF4J infoformerly known as SesameSAP Adaptive Server infoformer name: Sybase ASE
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