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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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 FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.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.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017
Primary database modelTime Series DBMSRelational DBMSKey-value storeDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score7.85
Rank#51  Overall
#8  Document stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Websiteiotdb.apache.orgetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestorejanusgraph.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestoredocs.janusgraph.org
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerGoogleLinux Foundation; originally developed as Titan by Aurelius
Initial release2018200820172017
Current release1.1.0, April 20237.2.4, September 20123.4, August 20190.6.3, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++GoJava
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
FreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsnonono
APIs and other access methodsJDBC
Native API
JDBCgRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
.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
Clojure
Java
Python
Server-side scripts infoStored proceduresyesnonoyes, Firebase Rules & Cloud Functionsyes
Triggersyesno infohooks for callbacks inside the server can be used.yes, watching key changesyes, with Cloud Functionsyes
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 replicasMulti-source replication
Source-replica replication
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknonoUsing Cloud Dataflowyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoyesACID
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 controlyesPluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.User authentification and security via Rexster Graph Server

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Apache IoTDBDrizzleetcdGoogle Cloud FirestoreJanusGraph infosuccessor of Titan
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