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DBMS > Apache IoTDB vs. Interbase vs. Prometheus vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Interbase vs. Prometheus vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonInterbase  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  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 FlinkLight-weight proven RDBMS infooriginally from BorlandOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.embarcadero.com/­products/­interbaseprometheus.iospark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.embarcadero.com/­products/­interbaseprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationEmbarcaderoApache Software Foundation
Initial release2018198420152014
Current release1.1.0, April 2023InterBase 2020, December 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCGoScala
Server operating systemsAll OS with a Java VM (>= 1.8)Android
iOS
Linux
OS X
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes
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 infoexport as XML data possibleno infoImport of XML data possibleno
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infoInterbase procedure and trigger languagenono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasInterbase Change Viewsyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistencynone
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnono

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Apache IoTDBInterbasePrometheusSpark SQL
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