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DBMS > Apache IoTDB vs. LMDB vs. Solr vs. TimesTen vs. WakandaDB

System Properties Comparison Apache IoTDB vs. LMDB vs. Solr vs. TimesTen vs. WakandaDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonLMDB  Xexclude from comparisonSolr  Xexclude from comparisonTimesTen  Xexclude from comparisonWakandaDB  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 high performant, light-weight, embedded key-value database libraryA widely used distributed, scalable search engine based on Apache LuceneIn-Memory RDBMS compatible to OracleWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelTime Series DBMSKey-value storeSearch engineRelational DBMSObject oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score1.31
Rank#163  Overall
#74  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteiotdb.apache.orgwww.symas.com/­symas-embedded-database-lmdbsolr.apache.orgwww.oracle.com/­database/­technologies/­related/­timesten.htmlwakanda.github.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.lmdb.tech/­docsolr.apache.org/­resources.htmldocs.oracle.com/­database/­timesten-18.1wakanda.github.io/­doc
DeveloperApache Software FoundationSymasApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005Wakanda SAS
Initial release20182011200619982012
Current release1.1.0, April 20230.9.32, January 20249.6.0, April 202411 Release 2 (11.2.2.8.0)2.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoApache Version 2commercialOpen Source infoAGPLv3, extended commercial license available
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 languageJavaCJavaC++, JavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
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
Linux
OS X
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesyes
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 indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languagenoSolr Parallel SQL Interfaceyesno
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Java
PL/SQL
JavaScript
Server-side scripts infoStored proceduresyesnoJava pluginsPL/SQLyes
Triggersyesnoyes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACIDACID
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.yesyesyesyesno
User concepts infoAccess controlyesnoyesfine grained access rights according to SQL-standardyes

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More resources
Apache IoTDBLMDBSolrTimesTenWakandaDB
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