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DBMS > Apache IoTDB vs. RRDtool vs. Sphinx vs. StarRocks

System Properties Comparison Apache IoTDB vs. RRDtool vs. Sphinx vs. StarRocks

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonRRDtool  Xexclude from comparisonSphinx  Xexclude from comparisonStarRocks  Xexclude from comparison
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 FlinkIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.Open source search engine for searching in data from different sources, e.g. relational databasesAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelTime Series DBMSTime Series DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.90
Rank#132  Overall
#11  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.93
Rank#198  Overall
#93  Relational DBMS
Websiteiotdb.apache.orgoss.oetiker.ch/­rrdtoolsphinxsearch.comwww.starrocks.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmloss.oetiker.ch/­rrdtool/­docsphinxsearch.com/­docsdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperApache Software FoundationTobias OetikerSphinx Technologies Inc.The Linux Foundation infosince Feb 2023
Initial release2018199920012020
Current release1.1.0, April 20231.8.0, 20223.5.1, February 20233.3, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPL V2 and FLOSSOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC infoImplementations in Java (e.g. RRD4J) and C# availableC++C++, Java
Server operating systemsAll OS with a Java VM (>= 1.8)HP-UX
Linux
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesNumeric data onlynoyes
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 infoExporting into and restoring from XML files possibleno
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
Native API
in-process shared library
Pipes
Proprietary protocolJDBC
MySQL protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Java
Server-side scripts infoStored proceduresyesnonouser defined functions
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyes infoby using the rrdcached daemonyesyes
Durability infoSupport for making data persistentyesyesyes 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.yesyesno
User concepts infoAccess controlyesnonoRole based access control and fine grained access rights

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