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DBMS > Amazon Aurora vs. Apache Impala vs. atoti vs. Fujitsu Enterprise Postgres vs. Hazelcast

System Properties Comparison Amazon Aurora vs. Apache Impala vs. atoti vs. Fujitsu Enterprise Postgres vs. Hazelcast

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonatoti  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHazelcast  Xexclude from comparison
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.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSObject oriented DBMSRelational DBMSKey-value store
Secondary database modelsDocument storeDocument storeDocument store
Spatial DBMS
Document 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
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgatoti.iowww.postgresql.fastware.comhazelcast.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.atoti.iowww.postgresql.fastware.com/­product-manualshazelcast.org/­imdg/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaActiveViamPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyHazelcast
Initial release201520132008
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 20225.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infofree versions availablecommercialOpen Source infoApache Version 2; commercial licenses available
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++JavaCJava
Server operating systemshostedLinuxLinux
Windows
All OS with a Java VM
Data schemeyesyesyesschema-free
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 strategy
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsMultidimensional Expressions (MDX)yesSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
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++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducePythonuser defined functionsyes infoEvent Listeners, Executor Services
Triggersyesnoyesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding, horizontal partitioningpartitioning by range, list and by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorSource-replica replicationyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes, multi-version concurrency control (MVCC)yes
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.yesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardRole-based access control
More information provided by the system vendor
Amazon AuroraApache ImpalaatotiFujitsu Enterprise PostgresHazelcast
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Amazon AuroraApache ImpalaatotiFujitsu Enterprise PostgresHazelcast
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