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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonRiak KV  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 FlinkUltra-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.Distributed, fault tolerant key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.harperdb.iosphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latestsphinxsearch.com/­docs
DeveloperApache Software FoundationHarperDBOpenSource, formerly Basho TechnologiesSphinx Technologies Inc.
Initial release2018201720092001
Current release1.1.0, April 20233.1, August 20213.2.0, December 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoApache version 2, commercial enterprise editionOpen 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 languageJavaNode.jsErlangC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Linux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesdynamic schemaschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesnono
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 indexesyesyesrestrictedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP API
Native Erlang Interface
Proprietary protocol
Supported programming languagesC
C#
C++
Go
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
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1Erlangno
Triggersyesnoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)A table resides as a whole on one (or more) nodes in a clusterSharding 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 replicasyes infothe nodes on which a table resides can be definedselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes 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 controlyesAccess rights for users and rolesyes, using Riak Securityno

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Apache IoTDBHarperDBRiak KVSphinx
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