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DBMS > Apache IoTDB vs. etcd vs. Google Cloud Firestore vs. Hive vs. JanusGraph

System Properties Comparison Apache IoTDB vs. etcd vs. Google Cloud Firestore vs. Hive vs. JanusGraph

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHive  Xexclude from comparisonJanusGraph infosuccessor of Titan  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 FlinkA 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.data warehouse software for querying and managing large distributed datasets, built on HadoopA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017
Primary database modelTime Series DBMSKey-value storeDocument storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score7.64
Rank#54  Overall
#5  Key-value stores
Score8.96
Rank#48  Overall
#8  Document stores
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score1.91
Rank#135  Overall
#12  Graph DBMS
Websiteiotdb.apache.orgetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestorehive.apache.orgjanusgraph.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestorecwiki.apache.org/­confluence/­display/­Hive/­Homedocs.janusgraph.org
DeveloperApache Software FoundationGoogleApache Software Foundation infoinitially developed by FacebookLinux Foundation; originally developed as Titan by Aurelius
Initial release2018201720122017
Current release1.1.0, April 20233.4, August 20193.1.3, April 20220.6.3, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VMLinux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenonoSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
Native API
gRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.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
PHP
Python
Clojure
Java
Python
Server-side scripts infoStored proceduresyesnoyes, Firebase Rules & Cloud Functionsyes infouser defined functions and integration of map-reduceyes
Triggersyesyes, watching key changesyes, with Cloud Functionsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoUsing Cloud Dataflowyes infoquery execution via MapReduceyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesnoAccess 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, groups and rolesUser authentification and security via Rexster Graph Server

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More resources
Apache IoTDBetcdGoogle Cloud FirestoreHiveJanusGraph infosuccessor of Titan
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