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DBMS > Apache IoTDB vs. DataFS vs. Datomic vs. etcd vs. Google Cloud Firestore

System Properties Comparison Apache IoTDB vs. DataFS vs. Datomic vs. etcd vs. Google Cloud Firestore

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDataFS  Xexclude from comparisonDatomic  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Firestore  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 FlinkAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed reliable key-value storeCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.
Primary database modelTime Series DBMSObject oriented DBMSRelational DBMSKey-value storeDocument store
Secondary database modelsGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score7.36
Rank#53  Overall
#9  Document stores
Websiteiotdb.apache.orgnewdatabase.comwww.datomic.cometcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestore
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldev.mobiland.com/­Overview.xspdocs.datomic.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestore
DeveloperApache Software FoundationMobiland AGCognitectGoogle
Initial release2018201820122017
Current release1.1.0, April 20231.1.263, October 20221.0.6735, June 20233.4, August 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infolimited edition freeOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureGo
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
hosted
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLSQL-like query languagenononono
APIs and other access methodsJDBC
Native API
.NET Client API
Proprietary client DLL
WinRT client
RESTful HTTP APIgRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
VB.Net
Clojure
Java
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsnoyes, Firebase Rules & Cloud Functions
Triggersyesno, except callback-events from server when changes happenedBy using transaction functionsyes, watching key changesyes, with Cloud Functions
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Proprietary Sharding systemnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoBut extensive use of caching in the application peersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknononoUsing Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes inforecommended only for testing and developmentno
User concepts infoAccess controlyesWindows-ProfilenonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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More resources
Apache IoTDBDataFSDatomicetcdGoogle Cloud Firestore
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