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DBMS > Apache IoTDB vs. IRONdb vs. Sphinx vs. TypeDB

System Properties Comparison Apache IoTDB vs. IRONdb vs. Sphinx vs. TypeDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSphinx  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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 FlinkA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen source search engine for searching in data from different sources, e.g. relational databasesTypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.
Primary database modelTime Series DBMSTime Series DBMSSearch engineGraph DBMS infoThe type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS infoThe data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS infoThe type-theoretic data model of TypeDB subsumes the relational database model.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.70
Rank#230  Overall
#20  Graph DBMS
#8  Object oriented DBMS
#106  Relational DBMS
Websiteiotdb.apache.orgwww.circonus.com/solutions/time-series-database/sphinxsearch.comtypedb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedsphinxsearch.com/­docstypedb.com/­docs
DeveloperApache Software FoundationCirconus LLC.Sphinx Technologies Inc.Vaticle
Initial release2018201720012016
Current release1.1.0, April 2023V0.10.20, January 20183.5.1, February 20232.28.3, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsnoyes
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 indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
Native API
HTTP APIProprietary protocolgRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyesyes, in Luanono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodeSharding infoPartitioning is done manually, search queries against distributed index is supportedno
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasconfigurable replication factor, datacenter awarenoneSynchronous replication via raft
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
Immediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynononono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnono
User concepts infoAccess controlyesnonoyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Apache IoTDBIRONdbSphinxTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Apache IoTDBIRONdbSphinxTypeDB infoformerly named Grakn
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