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DBMS > Brytlyt vs. GridDB vs. HBase vs. Solr

System Properties Comparison Brytlyt vs. GridDB vs. HBase vs. Solr

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonGridDB  Xexclude from comparisonHBase  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSTime Series DBMSWide column storeSearch engine
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitebrytlyt.iogriddb.nethbase.apache.orgsolr.apache.org
Technical documentationdocs.brytlyt.iodocs.griddb.nethbase.apache.org/­book.htmlsolr.apache.org/­resources.html
DeveloperBrytlytToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2016201320082006
Current release5.0, August 20235.1, August 20222.3.4, January 20219.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAC++JavaJava
Server operating systemsLinux
OS X
Windows
LinuxLinux
Unix
Windows infousing Cygwin
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-free, schema definition possibleyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)noSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoyes infoCoprocessors in JavaJava plugins
Triggersyesyesyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelSingle row ACID (across millions of columns)optimistic locking
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.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes
More information provided by the system vendor
BrytlytGridDBHBaseSolr
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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BrytlytGridDBHBaseSolr
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