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DBMS > Apache IoTDB vs. Microsoft Access vs. Solr vs. WakandaDB

System Properties Comparison Apache IoTDB vs. Microsoft Access vs. Solr vs. WakandaDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSolr  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 FlinkMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)A widely used distributed, scalable search engine based on Apache LuceneWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelTime Series DBMSRelational DBMSSearch engineObject 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
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websiteiotdb.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accesssolr.apache.orgwakanda.github.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldeveloper.microsoft.com/­en-us/­accesssolr.apache.org/­resources.htmlwakanda.github.io/­doc
DeveloperApache Software FoundationMicrosoftApache Software FoundationWakanda SAS
Initial release2018199220062012
Current release1.1.0, April 20231902 (16.0.11328.20222), March 20199.6.0, April 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC++, JavaScript
Server operating systemsAll OS with a Java VM (>= 1.8)Windows infoNot a real database server, but making use of DLLsAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesyes 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.noyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyes infobut not compliant to any SQL standardSolr Parallel SQL Interfaceno
APIs and other access methodsJDBC
Native API
ADO.NET
DAO
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresyesyes infosince Access 2010 using the ACE-engineJava pluginsyes
Triggersyesyes infosince Access 2010 using the ACE-engineyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyesnone
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
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infobut no files for transaction loggingoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesno infoa simple user-level security was built in till version Access 2003yesyes

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More resources
Apache IoTDBMicrosoft AccessSolrWakandaDB
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