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DBMS > Amazon Aurora vs. Apache Impala vs. atoti vs. Hazelcast vs. Teradata Aster

System Properties Comparison Amazon Aurora vs. Apache Impala vs. atoti vs. Hazelcast vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonatoti  Xexclude from comparisonHazelcast  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A widely adopted in-memory data gridPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSObject oriented DBMSKey-value storeRelational DBMS
Secondary database modelsDocument storeDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgatoti.iohazelcast.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.atoti.iohazelcast.org/­imdg/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaActiveViamHazelcastTeradata
Initial release2015201320082005
Current release4.1.0, June 20225.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infofree versions availableOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava
Server operating systemshostedLinuxAll OS with a Java VMLinux
Data schemeyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesnoyes infothe object must implement a serialization strategyyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsMultidimensional Expressions (MDX)SQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
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
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducePythonyes infoEvent Listeners, Executor ServicesR packages
Triggersyesnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding, horizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryes infoReplicated Mapyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
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.yesnoyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlfine grained access rights according to SQL-standard

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More resources
Amazon AuroraApache ImpalaatotiHazelcastTeradata Aster
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