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DBMS > Apache IoTDB vs. Badger vs. etcd vs. Google Cloud Firestore vs. Kinetica

System Properties Comparison Apache IoTDB vs. Badger vs. etcd vs. Google Cloud Firestore vs. Kinetica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBadger  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionA lightweight IoT native database management system deployable on the device and syncing the collected data with the cloud and integrated with Hadoop and SparkAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A 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.Fully vectorized database across both GPUs and CPUs
Primary database modelTime Series DBMSKey-value storeKey-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#271  Overall
#20  Time Series DBMS
Score0.11
Rank#304  Overall
#44  Key-value stores
Score10.81
Rank#46  Overall
#5  Key-value stores
Score9.56
Rank#50  Overall
#7  Document stores
Score0.73
Rank#204  Overall
#99  Relational DBMS
Websiteiotdb.apache.orggithub.com/­dgraph-io/­badgeretcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestorewww.kinetica.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgeretcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestorewww.kinetica.com/­docs
DeveloperApache Software FoundationDGraph LabsGoogleKinetica
Initial release2018201720172012
Current release3.4, August 20197.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoGoC, C++
Server operating systemsAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
Windows infoexperimental
hostedLinux
Data schemeyesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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 indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like query languagenononoSQL-like DML and DDL statements
APIs and other access methodsJDBCgRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo.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
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononoyes, Firebase Rules & Cloud Functionsuser defined functions
Triggersnonoyes, watching key changesyes, with Cloud Functionsyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknonoUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency with synchronizing with the cloudnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoyesno
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.yesnonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlnononoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and roles on table level
More information provided by the system vendor
Apache IoTDBBadgeretcdGoogle Cloud FirestoreKinetica
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more
Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache IoTDBBadgeretcdGoogle Cloud FirestoreKinetica
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