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DBMS > GigaSpaces vs. HarperDB vs. Sphinx vs. Valentina Server

System Properties Comparison GigaSpaces vs. HarperDB vs. Sphinx vs. Valentina Server

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonHarperDB  Xexclude from comparisonSphinx  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Open source search engine for searching in data from different sources, e.g. relational databasesObject-relational database and reports server
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Document storeSearch engineRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.gigaspaces.comwww.harperdb.iosphinxsearch.comwww.valentina-db.net
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.harperdb.io/­docssphinxsearch.com/­docsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGigaspaces TechnologiesHarperDBSphinx Technologies Inc.Paradigma Software
Initial release2000201720011999
Current release15.5, September 20203.1, August 20213.5.1, February 20235.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercial infofree community edition availableOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetNode.jsC++
Server operating systemsLinux
macOS
Solaris
Windows
Linux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freedynamic schemayesyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesnoyes
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.no infoXML can be used for describing objects metadatano
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like data manipulation statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Proprietary protocolODBC
Supported programming languages.Net
C++
Java
Python
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1noyes
Triggersyes, event driven architecturenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infothe nodes on which a table resides can be definednone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlRole-based access controlAccess rights for users and rolesnofine grained access rights according to SQL-standard

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More resources
GigaSpacesHarperDBSphinxValentina Server
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