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DBMS > Apache IoTDB vs. Brytlyt vs. Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Solr

System Properties Comparison Apache IoTDB vs. Brytlyt vs. Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Solr

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBrytlyt  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSolr  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 GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSRelational DBMSDocument storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgbrytlyt.iofirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­synapse-analyticssolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.brytlyt.iofirebase.google.com/­docs/­databasedocs.microsoft.com/­azure/­synapse-analyticssolr.apache.org/­resources.html
DeveloperApache Software FoundationBrytlytGoogle infoacquired by Google 2014MicrosoftApache Software Foundation
Initial release20182016201220162006
Current release1.1.0, April 20235.0, August 20239.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and CUDAC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
hostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyesyes infosupports customizable data types and automatic typing
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 functionality.nonoyes
Secondary indexesyesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyesnoyesSolr Parallel SQL Interface
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
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java
JavaScript
Objective-C
C#
Java
PHP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesuser defined functions infoin PL/pgSQLlimited functionality with using 'rules'Transact SQLJava plugins
TriggersyesyesCallbacks are triggered when data changesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding, horizontal partitioningSharding
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 replicationyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACIDoptimistic locking
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.yesyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyes, based on authentication and database rulesyesyes

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More resources
Apache IoTDBBrytlytFirebase Realtime DatabaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSolr
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