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DBMS > Apache IoTDB vs. HarperDB vs. LokiJS vs. Microsoft Access

System Properties Comparison Apache IoTDB vs. HarperDB vs. LokiJS vs. Microsoft Access

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonLokiJS  Xexclude from comparisonMicrosoft Access  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 FlinkUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.In-memory JavaScript DBMSMicrosoft 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.)
Primary database modelTime Series DBMSDocument storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score0.49
Rank#260  Overall
#42  Document stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websiteiotdb.apache.orgwww.harperdb.iogithub.com/­techfort/­LokiJSwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docstechfort.github.io/­LokiJSdeveloper.microsoft.com/­en-us/­access
DeveloperApache Software FoundationHarperDBMicrosoft
Initial release2018201720141992
Current release1.1.0, April 20233.1, August 20211902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Sourcecommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsJavaScriptC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
server-less, requires a JavaScript environment (browser, Node.js)Windows infoNot a real database server, but making use of DLLs
Data schemeyesdynamic schemaschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesnoyes
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.nonono
Secondary indexesyesyesyes infovia viewsyes
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsnoyes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
Native API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JavaScript APIADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
JavaScriptC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1View functions in JavaScriptyes infosince Access 2010 using the ACE-engine
Triggersyesnoyesyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)A table resides as a whole on one (or more) nodes in a clusternonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infothe nodes on which a table resides can be definednonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistencynone
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsno infoatomic operations within a single collection possibleACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesAccess rights for users and rolesnono infoa simple user-level security was built in till version Access 2003

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More resources
Apache IoTDBHarperDBLokiJSMicrosoft Access
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