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DBMS > Apache IoTDB vs. FatDB vs. GigaSpaces vs. Sphinx

System Properties Comparison Apache IoTDB vs. FatDB vs. GigaSpaces vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFatDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSphinx  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA .NET NoSQL DBMS that can integrate with and extend SQL Server.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Search engine
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.gigaspaces.comsphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.gigaspaces.com/­latest/­landing.htmlsphinxsearch.com/­docs
DeveloperApache Software FoundationFatCloudGigaspaces TechnologiesSphinx Technologies Inc.
Initial release2018201220002001
Current release1.1.0, April 202315.5, September 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Java, C++, .NetC++
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsLinux
macOS
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-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.nono infoXML can be used for describing objects metadata
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServerSQL-99 for query and DML statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#.Net
C++
Java
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyes infovia applicationsyesno
Triggersyesyes infovia applicationsyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyes
User concepts infoAccess controlyesno infoCan implement custom security layer via applicationsRole-based access controlno

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More resources
Apache IoTDBFatDBGigaSpacesSphinx
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