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DBMS > Amazon Aurora vs. eXtremeDB vs. Hazelcast vs. Sphinx

System Properties Comparison Amazon Aurora vs. eXtremeDB vs. Hazelcast vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonNatively in-memory DBMS with options for persistency, high-availability and clusteringA widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Key-value storeSearch engine
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.50
Rank#49  Overall
#31  Relational DBMS
Score0.73
Rank#227  Overall
#104  Relational DBMS
#18  Time Series DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score6.03
Rank#60  Overall
#6  Search engines
Websiteaws.amazon.com/­rds/­aurorawww.mcobject.comhazelcast.comsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.mcobject.com/­docs/­extremedb.htmhazelcast.org/­imdg/­docssphinxsearch.com/­docs
DeveloperAmazonMcObjectHazelcastSphinx Technologies Inc.
Initial release2015200120082001
Current release8.2, 20215.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaC++
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
All OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesno
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.yesno infosupport of XML interfaces availableyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesyes infowith the option: eXtremeSQLSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
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
.Net
C
C#
C++
Java
Lua
Python
Scala
.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 proceduresyesyesyes infoEvent Listeners, Executor Servicesno
Triggersyesyes infoby defining eventsyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning / shardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlno
More information provided by the system vendor
Amazon AuroraeXtremeDBHazelcastSphinx
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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Amazon AuroraeXtremeDBHazelcastSphinx
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