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DBMS > Amazon Aurora vs. Apache Impala vs. EXASOL vs. Hazelcast vs. Sphinx

System Properties Comparison Amazon Aurora vs. Apache Impala vs. EXASOL vs. Hazelcast vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonEXASOL  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value storeSearch engine
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
Score9.05
Rank#49  Overall
#31  Relational DBMS
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score2.47
Rank#119  Overall
#57  Relational DBMS
Score7.66
Rank#54  Overall
#5  Key-value stores
Score6.06
Rank#61  Overall
#6  Search engines
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.exasol.comhazelcast.comsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmlwww.exasol.com/­resourceshazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaExasolHazelcastSphinx Technologies Inc.
Initial release20152013200020082001
Current release4.1.0, June 20225.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence 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++JavaC++
Server operating systemshostedLinuxAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.yesnonoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
.Net
JDBC
ODBC
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol
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/ODBCJava
Lua
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reduceuser defined functionsyes infoEvent Listeners, Executor Servicesno
Triggersyesnoyesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factoryes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes infoHadoop integrationyesno
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 integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 KerberosAccess rights for users, groups and roles according to SQL-standardRole-based access controlno

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More resources
Amazon AuroraApache ImpalaEXASOLHazelcastSphinx
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