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DBMS > Apache Phoenix vs. Brytlyt vs. GBase vs. GridDB vs. Pinecone

System Properties Comparison Apache Phoenix vs. Brytlyt vs. GBase vs. GridDB vs. Pinecone

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBrytlyt  Xexclude from comparisonGBase  Xexclude from comparisonGridDB  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseScalable 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 modelRelational DBMSRelational 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
Score2.06
Rank#123  Overall
#58  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
Websitephoenix.apache.orgbrytlyt.iowww.gbase.cngriddb.netwww.pinecone.io
Technical documentationphoenix.apache.orgdocs.brytlyt.iodocs.griddb.netdocs.pinecone.io/­docs/­overview
DeveloperApache Software FoundationBrytlytGeneral Data Technology Co., Ltd.Toshiba CorporationPinecone Systems, Inc
Initial release20142016200420132019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.0, August 2023GBase 8a, GBase 8s, GBase 8c5.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 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

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Implementation languageJavaC, C++ and CUDAC, Java, PythonC++
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
LinuxLinuxhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
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 methodsJDBCADO.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
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.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 proceduresuser defined functionsuser defined functions infoin PL/pgSQLuser defined functionsno
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesyesno
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.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardyesAccess rights for users can be defined per database
More information provided by the system vendor
Apache PhoenixBrytlytGBaseGridDBPinecone
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PhoenixBrytlytGBaseGridDBPinecone
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