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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEJDB  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 FlinkEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Automatically 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 storeDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Websiteiotdb.apache.orggithub.com/­Softmotions/­ejdbcloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperApache Software FoundationSoftmotionsGoogleCirconus LLC.
Initial release2018201220082017
Current release1.1.0, April 2023V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)server-lesshostedLinux
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, 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.nonono
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJDBC
Native API
in-process shared librarygRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.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
TriggersyesnoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingAutomatic, 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 replicasnoneMulti-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
Immediate 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 integritynono infotypically not needed, however similar functionality with collection joins possibleyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache IoTDBEJDBGoogle Cloud DatastoreIRONdb
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