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

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

Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDatabricks  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Cloud-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 modelRelational DBMSDocument store
Relational DBMS
Document storeRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  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
Websitebrytlyt.iowww.databricks.comfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­synapse-analyticssolr.apache.org
Technical documentationdocs.brytlyt.iodocs.databricks.comfirebase.google.com/­docs/­databasedocs.microsoft.com/­azure/­synapse-analyticssolr.apache.org/­resources.html
DeveloperBrytlytDatabricksGoogle infoacquired by Google 2014MicrosoftApache Software Foundation
Initial release20162013201220162006
Current release5.0, August 20239.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAC++Java
Server operating systemsLinux
OS X
Windows
hostedhostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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.yes infospecific XML-type available, but no XML query functionality.yesnonoyes
Secondary indexesyesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyeswith Databricks SQLnoyesSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Python
R
Scala
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 proceduresuser defined functions infoin PL/pgSQLuser defined functions and aggregateslimited functionality with using 'rules'Transact SQLJava plugins
TriggersyesCallbacks are triggered when data changesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono 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 dataACIDACIDyesACIDoptimistic 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.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesyesyes
More information provided by the system vendor
BrytlytDatabricksFirebase Realtime DatabaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
BrytlytDatabricksFirebase Realtime DatabaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSolr
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