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DBMS > Apache IoTDB vs. PouchDB vs. Splice Machine vs. SQLite

System Properties Comparison Apache IoTDB vs. PouchDB vs. Splice Machine vs. SQLite

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonPouchDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQLite  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 FlinkJavaScript DBMS with an API inspired by CouchDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkWidely used embeddable, in-process RDBMS
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#183  Overall
#15  Time Series DBMS
Score2.70
Rank#114  Overall
#22  Document stores
Score0.54
Rank#257  Overall
#118  Relational DBMS
Score118.16
Rank#10  Overall
#7  Relational DBMS
Websiteiotdb.apache.orgpouchdb.comsplicemachine.comwww.sqlite.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlpouchdb.com/­guidessplicemachine.com/­how-it-workswww.sqlite.org/­docs.html
DeveloperApache Software FoundationApache Software FoundationSplice MachineDwayne Richard Hipp
Initial release2018201220142000
Current release1.1.0, April 20237.1.1, June 20193.1, March 20213.45.2  (12 March 2024), March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoAGPL 3.0, commercial license availableOpen Source infoPublic Domain
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScriptJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Solaris
Windows
server-less
Data schemeyesschema-freeyesyes infodynamic column types
Typing infopredefined data types such as float or dateyesnoyesyes infonot rigid because of 'dynamic typing' concept.
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 infovia viewsyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyes infoSQL-92 is not fully supported
APIs and other access methodsJDBC
Native API
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
Native Spark Datasource
ODBC
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
Server-side scripts infoStored proceduresyesView functions in JavaScriptyes infoJavano
Triggersyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infowith a proxy-based framework, named couchdb-loungeShared Nothhing Auto-Sharding, Columnar Partitioningnone
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 infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes infovia file-system locks
Durability infoSupport for making data persistentyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardno

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