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DBMS > Apache IoTDB vs. Apache Kylin vs. etcd vs. HBase vs. Solr

System Properties Comparison Apache IoTDB vs. Apache Kylin vs. etcd vs. HBase vs. Solr

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Kylin  Xexclude from comparisonetcd  Xexclude from comparisonHBase  Xexclude from comparisonSolr  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 FlinkA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackA distributed reliable key-value storeWide-column store based on Apache Hadoop and on concepts of BigTableA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMSKey-value storeWide column storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score41.02
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgkylin.apache.orgetcd.io
github.com/­etcd-io/­etcd
hbase.apache.orgsolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlkylin.apache.org/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmlsolr.apache.org/­resources.html
DeveloperApache Software FoundationApache Software Foundation, originally contributed from eBay IncApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2018201520082006
Current release1.1.0, April 20233.1.0, July 20203.4, August 20192.3.4, January 20219.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGoJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-freeschema-free, schema definition possibleyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesnooptions to bring your own types, AVROyes infosupports customizable data types and automatic typing
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.nonononoyes
Secondary indexesyesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageANSI SQL for queries (using Apache Calcite)nonoSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnoyes infoCoprocessors in JavaJava plugins
Triggersyesyes, watching key changesyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoSingle row ACID (across millions of columns)optimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlyesnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes

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Apache IoTDBApache KylinetcdHBaseSolr
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