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DBMS > Apache IoTDB vs. ArangoDB vs. Kinetica vs. Sphinx

System Properties Comparison Apache IoTDB vs. ArangoDB vs. Kinetica vs. Sphinx

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonArangoDB  Xexclude from comparisonKinetica  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 FlinkNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.Fully vectorized database across both GPUs and CPUsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSDocument store
Graph DBMS
Key-value store
Search engine
Relational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score3.26
Rank#88  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteiotdb.apache.orgarangodb.comwww.kinetica.comsphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.arangodb.comdocs.kinetica.comsphinxsearch.com/­docs
Social network pagesLinkedInTwitterYouTubeFacebookInstagram
DeveloperApache Software FoundationArangoDB Inc.KineticaSphinx Technologies Inc.
Initial release2018201220122001
Current release1.1.0, April 20233.11.5, November 20237.1, August 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial license (Enterprise) availablecommercialOpen 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++C, C++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-free infoautomatically recognizes schema within a collectionyesyes
Typing infopredefined data types such as float or dateyesyes infostring, double, boolean, list, hashyesno
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
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
C++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesJavaScriptuser defined functionsno
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infosince version 2.0ShardingSharding 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 replicasSource-replica replication with configurable replication factorSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno infocan be done with stored procedures in JavaScriptnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes inforelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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 infoGPU vRAM or System RAM
User concepts infoAccess controlyesyesAccess rights for users and roles on table levelno
More information provided by the system vendor
Apache IoTDBArangoDBKineticaSphinx
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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Apache IoTDBArangoDBKineticaSphinx
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