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DBMS > Amazon Aurora vs. BigObject vs. Hazelcast vs. LMDB vs. Sphinx

System Properties Comparison Amazon Aurora vs. BigObject vs. Hazelcast vs. LMDB vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonBigObject  Xexclude from comparisonHazelcast  Xexclude from comparisonLMDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for real-time computations and queriesA widely adopted in-memory data gridA high performant, light-weight, embedded key-value database libraryOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedKey-value storeKey-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
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score1.99
Rank#125  Overall
#21  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­rds/­aurorabigobject.iohazelcast.comwww.symas.com/­symas-embedded-database-lmdbsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.bigobject.iohazelcast.org/­imdg/­docswww.lmdb.tech/­docsphinxsearch.com/­docs
DeveloperAmazonBigObject, Inc.HazelcastSymasSphinx Technologies Inc.
Initial release20152015200820112001
Current release5.3.6, November 20230.9.32, January 20243.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2; commercial licenses availableOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++
Server operating systemshostedLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VMLinux
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeschema-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.yesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query languagenoSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
fluentd
ODBC
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++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesLuayes infoEvent Listeners, Executor Servicesnono
Triggersyesnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoReplicated Mapnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoRole-based access controlnono

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More resources
Amazon AuroraBigObjectHazelcastLMDBSphinx
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