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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHarperDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
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.Microsoft 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.)Transactional SQL-on-Hadoop DBMS
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational 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
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websiteiotdb.apache.orgwww.harperdb.iowww.microsoft.com/­en-us/­microsoft-365/­accesstrafodion.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.harperdb.io/­docsdeveloper.microsoft.com/­en-us/­accesstrafodion.apache.org/­documentation.html
DeveloperApache Software FoundationHarperDBMicrosoftApache Software Foundation, originally developed by HP
Initial release2018201719922014
Current release1.1.0, April 20233.1, August 20211902 (16.0.11328.20222), March 20192.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC++C++, Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows infoNot a real database server, but making use of DLLsLinux
Data schemeyesdynamic schemayesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like data manipulation statementsyes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBC
Native API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
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
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1yes infosince Access 2010 using the ACE-engineJava Stored Procedures
Triggersyesnoyes infosince Access 2010 using the ACE-engineno
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 clusternoneSharding
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 definednoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByes infobut no files for transaction loggingyes
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 2003fine grained access rights according to SQL-standard

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More resources
Apache IoTDBHarperDBMicrosoft AccessTrafodion
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