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DBMS > Apache IoTDB vs. Bangdb vs. Google Cloud Datastore vs. IRONdb

System Properties Comparison Apache IoTDB vs. Bangdb vs. Google Cloud Datastore vs. IRONdb

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. 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 FlinkConverged and high performance database for device data, events, time series, document and graphAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Document storeTime Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websiteiotdb.apache.orgbangdb.comcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperApache Software FoundationSachin Sinha, BangDBGoogleCirconus LLC.
Initial release2018201220082017
Current release1.1.0, April 2023BangDB 2.0, October 2021V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C and C++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedLinux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyes, details hereyes infotext, numeric, histograms
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.nononono
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyesno
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyesnousing Google App Engineyes, in Lua
Triggersyesyes, Notifications (with Streaming only)Callbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication using Paxosconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Tunable consistency, set CAP knob accordinglyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modenono
User concepts infoAccess controlyesyes (enterprise version only)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache IoTDBBangdbGoogle Cloud DatastoreIRONdb
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