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DBMS > Apache IoTDB vs. Riak KV vs. RisingWave vs. Sphinx

System Properties Comparison Apache IoTDB vs. Riak KV vs. RisingWave vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonRiak KV  Xexclude from comparisonRisingWave  Xexclude from comparisonSphinx  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 FlinkDistributed, fault tolerant key-value storeA distributed RDBMS for stream processing, wire-compatible with PostgreSQLOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score3.84
Rank#76  Overall
#9  Key-value stores
Score0.61
Rank#237  Overall
#111  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.risingwave.com/­databasesphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.risingwave.com/­docs/­current/­introsphinxsearch.com/­docs
DeveloperApache Software FoundationOpenSource, formerly Basho TechnologiesRisingWave LabsSphinx Technologies Inc.
Initial release2018200920222001
Current release1.1.0, April 20233.2.0, December 20221.2, September 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaErlangRustC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Docker
Linux
macOS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoStandard SQL-types and JSONno
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.nonono
Secondary indexesyesrestrictedyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoyesSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
HTTP API
Native Erlang Interface
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesErlangUDFs in Python or Javano
Triggersyesyes infopre-commit hooks and post-commit hooksnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infono "single point of failure"Sharding 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 factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storednono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 controlyesyes, using Riak SecurityUsers and Rolesno

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More resources
Apache IoTDBRiak KVRisingWaveSphinx
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