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DBMS > Badger vs. Brytlyt vs. Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Vitess

System Properties Comparison Badger vs. Brytlyt vs. Firebase Realtime Database vs. Microsoft Azure Synapse Analytics vs. Vitess

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBrytlyt  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable 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 ServerScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelKey-value storeRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerbrytlyt.iofirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­synapse-analyticsvitess.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.brytlyt.iofirebase.google.com/­docs/­databasedocs.microsoft.com/­azure/­synapse-analyticsvitess.io/­docs
DeveloperDGraph LabsBrytlytGoogle infoacquired by Google 2014MicrosoftThe Linux Foundation, PlanetScale
Initial release20172016201220162013
Current release5.0, August 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, C++ and CUDAC++Go
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
hostedhostedDocker
Linux
macOS
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.nono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyesnoyesyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesGo.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java
JavaScript
Objective-C
C#
Java
PHP
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLlimited functionality with using 'rules'Transact SQLyes infoproprietary syntax
TriggersnoyesCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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 controlnofine grained access rights according to SQL-standardyes, based on authentication and database rulesyesUsers with fine-grained authorization concept infono user groups or roles

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More resources
BadgerBrytlytFirebase Realtime DatabaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseVitess
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