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DBMS > Apache IoTDB vs. Citus vs. CockroachDB vs. Firebase Realtime Database vs. Hazelcast

System Properties Comparison Apache IoTDB vs. Citus vs. CockroachDB vs. Firebase Realtime Database vs. Hazelcast

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonCockroachDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHazelcast  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 FlinkScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A widely adopted in-memory data grid
Primary database modelTime Series DBMSRelational DBMSRelational DBMSDocument storeKey-value store
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Websiteiotdb.apache.orgwww.citusdata.comwww.cockroachlabs.comfirebase.google.com/­products/­realtime-databasehazelcast.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comwww.cockroachlabs.com/­docsfirebase.google.com/­docs/­databasehazelcast.org/­imdg/­docs
DeveloperApache Software FoundationCockroach LabsGoogle infoacquired by Google 2014Hazelcast
Initial release20182010201520122008
Current release1.1.0, April 20238.1, December 201824.1.0, May 20245.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availableOpen Source infoApache 2.0, commercial license availablecommercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCGoJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS
Windows
hostedAll OS with a Java VM
Data schemeyesyesdynamic schemaschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyes infospecific XML type available, but no XML query functionalitynonoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionsyes, wire compatible with PostgreSQLnoSQL-like query language
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCAndroid
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Java
JavaScript
Objective-C
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nolimited functionality with using 'rules'yes infoEvent Listeners, Executor Services
TriggersyesyesnoCallbacks are triggered when data changesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using RAFTyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDyesone or two-phase-commit; repeatable reads; read commited
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
User concepts infoAccess controlyesfine grained access rights according to SQL-standardRole-based access controlyes, based on authentication and database rulesRole-based access control

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More resources
Apache IoTDBCitusCockroachDBFirebase Realtime DatabaseHazelcast
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