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DBMS > Apache IoTDB vs. BoltDB vs. FileMaker vs. GridDB vs. Heroic

System Properties Comparison Apache IoTDB vs. BoltDB vs. FileMaker vs. GridDB vs. Heroic

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBoltDB  Xexclude from comparisonFileMaker  Xexclude from comparisonGridDB  Xexclude from comparisonHeroic  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 FlinkAn embedded key-value store for Go.FileMaker is a cross-platform RDBMS that includes a GUI frontend.Scalable in-memory time series database optimized for IoT and Big DataTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch
Primary database modelTime Series DBMSKey-value storeRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.80
Rank#215  Overall
#31  Key-value stores
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Websiteiotdb.apache.orggithub.com/­boltdb/­boltwww.claris.com/­filemakergriddb.netgithub.com/­spotify/­heroic
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.claris.com/­resources/­documentationdocs.griddb.netspotify.github.io/­heroic
DeveloperApache Software FoundationClaris infoa subsidiary of AppleToshiba CorporationSpotify
Initial release20182013198320132014
Current release1.1.0, April 202319.4.1, November 20215.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicensecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Solaris
Windows
iOS infoclient part only
Linux
OS X
Windows
Linux
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nonoyes infoA http query request can return the data in XML formatnono
Secondary indexesyesnoyesyesyes infovia Elasticsearch
SQL infoSupport of SQLSQL-like query languagenoyes infovia pluginsSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
Native API
Filemaker WebDirect
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
GoPHPC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoyesnono
Triggersyesnoyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneSource-replica replication, warm standby infosince Version 14Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlyesnosimple rights management via user accounts and connection to external directory servicesAccess rights for users can be defined per database
More information provided by the system vendor
Apache IoTDBBoltDBFileMakerGridDBHeroic
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache IoTDBBoltDBFileMakerGridDBHeroic
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