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DBMS > Brytlyt vs. Firebase Realtime Database vs. Google Cloud Spanner vs. Trafodion

System Properties Comparison Brytlyt vs. Firebase Realtime Database vs. Google Cloud Spanner vs. Trafodion

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable 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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Transactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Websitebrytlyt.iofirebase.google.com/­products/­realtime-databasecloud.google.com/­spannertrafodion.apache.org
Technical documentationdocs.brytlyt.iofirebase.google.com/­docs/­databasecloud.google.com/­spanner/­docstrafodion.apache.org/­documentation.html
DeveloperBrytlytGoogle infoacquired by Google 2014GoogleApache Software Foundation, originally developed by HP
Initial release2016201220172014
Current release5.0, August 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAC++, Java
Server operating systemsLinux
OS X
Windows
hostedhostedLinux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesnoyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Java
JavaScript
Objective-C
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLlimited functionality with using 'rules'noJava Stored Procedures
TriggersyesCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
BrytlytFirebase Realtime DatabaseGoogle Cloud SpannerTrafodion
DB-Engines blog posts

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Recent citations in the news

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

London data analytics startup Brytlyt raises €4.43M from Amsterdam-based Finch Capital, others
22 December 2021, Silicon Canals

Brytlyt becomes NVIDIA Inception Premier Partner
31 January 2023, PR Newswire

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

Bringing GPUs To Bear On Bog Standard Relational Databases
26 February 2018, The Next Platform

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Don't be like these 900+ websites and expose millions of passwords via Firebase
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Google Firebase may have exposed 125M records from misconfigurations
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