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DBMS > Apache IoTDB vs. FileMaker vs. HarperDB vs. IBM Db2 Event Store

System Properties Comparison Apache IoTDB vs. FileMaker vs. HarperDB vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFileMaker  Xexclude from comparisonHarperDB  Xexclude from comparisonIBM Db2 Event Store  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 FlinkFileMaker is a cross-platform RDBMS that includes a GUI frontend.Ultra-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.Distributed Event Store optimized for Internet of Things use cases
Primary database modelTime Series DBMSRelational DBMSDocument storeEvent Store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score48.20
Rank#20  Overall
#14  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websiteiotdb.apache.orgwww.claris.com/­filemakerwww.harperdb.iowww.ibm.com/­products/­db2-event-store
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.claris.com/­resources/­documentationdocs.harperdb.io/­docswww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software FoundationClaris infoa subsidiary of AppleHarperDBIBM
Initial release2018198320172017
Current release1.1.0, April 202319.4.1, November 20213.1, August 20212.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree community edition availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)iOS infoclient part only
Linux
OS X
Windows
Linux
OS X
Linux infoLinux, macOS, Windows for the developer addition
Data schemeyesyesdynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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.noyes infoA http query request can return the data in XML formatnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyes infovia pluginsSQL-like data manipulation statementsyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
Native API
Filemaker WebDirect
JDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
PHP.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++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Server-side scripts infoStored proceduresyesyesCustom Functions infosince release 3.1yes
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication, warm standby infosince Version 14yes infothe nodes on which a table resides can be definedActive-active shard replication
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
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesyes, using LMDBYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyessimple rights management via user accounts and connection to external directory servicesAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBFileMakerHarperDBIBM Db2 Event Store
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