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DBMS > AgensGraph vs. Brytlyt vs. GBase vs. GridDB vs. Pinecone

System Properties Comparison AgensGraph vs. Brytlyt vs. GBase vs. GridDB vs. Pinecone

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonBrytlyt  Xexclude from comparisonGBase  Xexclude from comparisonGridDB  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLScalable 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.Scalable in-memory time series database optimized for IoT and Big DataA managed, cloud-native vector database
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMSTime Series DBMSVector DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Websitebitnine.net/­agensgraphbrytlyt.iowww.gbase.cngriddb.netwww.pinecone.io
Technical documentationbitnine.net/­documentationdocs.brytlyt.iodocs.griddb.netdocs.pinecone.io/­docs/­overview
DeveloperBitnine Global Inc.BrytlytGeneral Data Technology Co., Ltd.Toshiba CorporationPinecone Systems, Inc
Initial release20162016200420132019
Current release2.1, December 20185.0, August 2023GBase 8a, GBase 8s, GBase 8c5.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, C++ and CUDAC, Java, PythonC++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
LinuxLinuxhosted
Data schemedepending on used data modelyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestampString, Number, Boolean
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.yesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyesStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Python
Server-side scripts infoStored proceduresyesuser defined functions infoin PL/pgSQLuser defined functionsno
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancehorizontal partitioning (by range, list and hash) and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID at container level
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.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyesAccess rights for users can be defined per database
More information provided by the system vendor
AgensGraphBrytlytGBaseGridDBPinecone
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
AgensGraphBrytlytGBaseGridDBPinecone
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