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DBMS > Hazelcast vs. Microsoft Azure Table Storage vs. OrigoDB vs. Sphinx

System Properties Comparison Hazelcast vs. Microsoft Azure Table Storage vs. OrigoDB vs. Sphinx

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrigoDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsA fully ACID in-memory object graph databaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeWide column storeDocument store
Object oriented DBMS
Search engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Score0.00
Rank#385  Overall
#54  Document stores
#21  Object oriented DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websitehazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tablesorigodb.comsphinxsearch.com
Technical documentationhazelcast.org/­imdg/­docsorigodb.com/­docssphinxsearch.com/­docs
DeveloperHazelcastMicrosoftRobert Friberg et alSphinx Technologies Inc.
Initial release200820122009 infounder the name LiveDB2001
Current release5.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#C++
Server operating systemsAll OS with a Java VMhostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsno
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.yes infothe object must implement a serialization strategynono infocan be achieved using .NET
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenonoSQL-like query language (SphinxQL)
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP API.NET Client API
HTTP API
LINQ
Proprietary protocol
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.NetC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnoyesno
Triggersyes infoEventsnoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizedSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes 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.yesnoyes
User concepts infoAccess controlRole-based access controlAccess rights based on private key authentication or shared access signaturesRole based authorizationno

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HazelcastMicrosoft Azure Table StorageOrigoDBSphinx
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