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DBMS > Apache IoTDB vs. Citus vs. Databricks vs. Solr vs. TimesTen

System Properties Comparison Apache IoTDB vs. Citus vs. Databricks vs. Solr vs. TimesTen

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonSolr  Xexclude from comparisonTimesTen  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 FlinkScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A widely used distributed, scalable search engine based on Apache LuceneIn-Memory RDBMS compatible to Oracle
Primary database modelTime Series DBMSRelational DBMSDocument store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteiotdb.apache.orgwww.citusdata.comwww.databricks.comsolr.apache.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comdocs.databricks.comsolr.apache.org/­resources.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software FoundationDatabricksApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182010201320061998
Current release1.1.0, April 20238.1, December 20189.6.0, April 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.noyes infospecific XML type available, but no XML query functionalityyesyesno
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionswith Databricks SQLSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregatesJava pluginsPL/SQL
Triggersyesyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingnone
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 infoother methods possible by using 3rd party extensionsyesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IoTDBCitusDatabricksSolrTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBCitusDatabricksSolrTimesTen
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