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DBMS > Apache IoTDB vs. KeyDB vs. SiteWhere vs. Sphinx

System Properties Comparison Apache IoTDB vs. KeyDB vs. SiteWhere vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKeyDB  Xexclude from comparisonSiteWhere  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 FlinkAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsM2M integration platform for persisting/querying time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSKey-value storeTime Series DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.63
Rank#232  Overall
#32  Key-value stores
Score0.07
Rank#347  Overall
#33  Time Series DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orggithub.com/­Snapchat/­KeyDB
keydb.dev
github.com/­sitewhere/­sitewheresphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.keydb.devsitewhere1.sitewhere.io/­index.htmlsphinxsearch.com/­docs
DeveloperApache Software FoundationEQ Alpha Technology Ltd.SiteWhereSphinx Technologies Inc.
Initial release2018201920102001
Current release1.1.0, April 20233.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD-3Open Source infoCommon Public Attribution License Version 1.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freepredefined schemeyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesno
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 indexesyesyes infoby using the Redis Search modulenoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenonoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
Proprietary protocol infoRESP - REdis Serialization ProtocoHTTP RESTProprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesLuano
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infobased on HBaseSharding 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 replicasMulti-source replication
Source-replica replication
selectable replication factor infobased on HBasenone
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
Eventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoOptimistic locking, atomic execution of commands blocks and scriptsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes 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.yesyesno
User concepts infoAccess controlyessimple password-based access control and ACLUsers with fine-grained authorization conceptno

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More resources
Apache IoTDBKeyDBSiteWhereSphinx
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