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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHazelcast  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed 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 FlinkScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLCloud-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 gridAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSRelational DBMSDocument storeKey-value storeDocument store
Graph DBMS
Key-value store
Wide column 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
Score14.29
Rank#39  Overall
#6  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Websiteiotdb.apache.orgwww.citusdata.comfirebase.google.com/­products/­realtime-databasehazelcast.comsqrrl.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comfirebase.google.com/­docs/­databasehazelcast.org/­imdg/­docs
DeveloperApache Software FoundationGoogle infoacquired by Google 2014HazelcastAmazon infooriginally Sqrrl Data, Inc.
Initial release20182010201220082012
Current release1.1.0, April 20238.1, December 20185.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedAll OS with a Java VMLinux
Data schemeyesyesschema-freeschema-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 functionalitynoyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionsnoSQL-like query languageno
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
JavaScript
Objective-C
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.limited functionality with using 'rules'yes infoEvent Listeners, Executor Servicesno
TriggersyesyesCallbacks are triggered when data changesyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingSharding infomaking use of Hadoop
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 extensionsyes infoReplicated Mapselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesone or two-phase-commit; repeatable reads; read commitedAtomic updates per row, document, or graph entity
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.yesnoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyes, based on authentication and database rulesRole-based access controlCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache IoTDBCitusFirebase Realtime DatabaseHazelcastSqrrl
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