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DBMS > Apache Impala vs. Apache IoTDB vs. Solr vs. TimesTen vs. Yanza

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Solr vs. TimesTen vs. Yanza

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonSolr  Xexclude from comparisonTimesTen  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopAn 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 widely used distributed, scalable search engine based on Apache LuceneIn-Memory RDBMS compatible to OracleTime Series DBMS for IoT Applications
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMSTime Series DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgsolr.apache.orgwww.oracle.com/­database/­technologies/­related/­timesten.htmlyanza.com
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsolr.apache.org/­resources.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005Yanza
Initial release20132018200619982015
Current release4.1.0, June 20221.1.0, April 20239.6.0, April 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2commercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)All 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
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesno
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.nonoyesnono
Secondary indexesyesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSolr Parallel SQL Interfaceyesno
APIs and other access methodsJDBC
ODBC
JDBC
Native API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
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
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesJava pluginsPL/SQLno
Triggersnoyesyes infoUser configurable commands triggered on index changesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpointsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesyesfine grained access rights according to SQL-standardno

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More resources
Apache ImpalaApache IoTDBSolrTimesTenYanza
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