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DBMS > Brytlyt vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. openGauss

System Properties Comparison Brytlyt vs. EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. openGauss

Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonopenGauss  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score1.06
Rank#184  Overall
#84  Relational DBMS
Websitebrytlyt.iowww.esgyn.cnfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtablegitee.com/­opengauss
opengauss.org
Technical documentationdocs.brytlyt.iofirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docsdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
DeveloperBrytlytEsgynGoogle infoacquired by Google 2014GoogleHuawei and openGauss community
Initial release20162015201220152019
Current release5.0, August 20233.0, March 2022
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source
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 languageC, C++ and CUDAC++, JavaC, C++, Java
Server operating systemsLinux
OS X
Windows
LinuxhostedhostedLinux
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesyesnonoANSI SQL 2011
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
All languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Java
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLJava Stored Procedureslimited functionality with using 'rules'noyes
TriggersyesnoCallbacks are triggered when data changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by range, list and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyesno
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 consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesAtomic single-row operationsACID
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine 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)Access rights for users, groups and roles according to SQL-standard

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More resources
BrytlytEsgynDBFirebase Realtime DatabaseGoogle Cloud BigtableopenGauss
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