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DBMS > Brytlyt vs. GBase vs. Google Cloud Bigtable vs. GridDB

System Properties Comparison Brytlyt vs. GBase vs. Google Cloud Bigtable vs. GridDB

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Time Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitebrytlyt.iowww.gbase.cncloud.google.com/­bigtablegriddb.net
Technical documentationdocs.brytlyt.iocloud.google.com/­bigtable/­docsdocs.griddb.net
DeveloperBrytlytGeneral Data Technology Co., Ltd.GoogleToshiba Corporation
Initial release2016200420152013
Current release5.0, August 2023GBase 8a, GBase 8s, GBase 8c5.1, August 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAC, Java, PythonC++
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes infonumerical, string, blob, geometry, boolean, timestamp
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.yesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesStandard with numerous extensionsnoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C#C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functionsnono
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACID at container level
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.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per database
More information provided by the system vendor
BrytlytGBaseGoogle Cloud BigtableGridDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
BrytlytGBaseGoogle Cloud BigtableGridDB
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