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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonHeroic  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 FlinkHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchMicrosoft 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 storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score93.76
Rank#12  Overall
#8  Relational DBMS
Websiteiotdb.apache.orgwww.harperdb.iogithub.com/­spotify/­heroicwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docsspotify.github.io/­heroicdeveloper.microsoft.com/­en-us/­access
DeveloperApache Software FoundationHarperDBSpotifyMicrosoft
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 Source infoApache 2.0commercial 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.jsJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
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 typesyesyes
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 Elasticsearchyes
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
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.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
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1noyes infosince Access 2010 using the ACE-engine
Triggersyesnonoyes 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 clusterShardingnone
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 definedyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes 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.yesyesno
User concepts infoAccess controlyesAccess rights for users and rolesno infoa simple user-level security was built in till version Access 2003

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More resources
Apache IoTDBHarperDBHeroicMicrosoft Access
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