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DBMS > BigObject vs. Blueflood vs. Cachelot.io vs. GridDB

System Properties Comparison BigObject vs. Blueflood vs. Cachelot.io vs. GridDB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonBlueflood  Xexclude from comparisonCachelot.io  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable TimeSeries DBMS based on CassandraIn-memory caching systemScalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMSKey-value storeTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitebigobject.ioblueflood.iocachelot.iogriddb.net
Technical documentationdocs.bigobject.iogithub.com/­rax-maas/­blueflood/­wikidocs.griddb.net
DeveloperBigObject, Inc.RackspaceToshiba Corporation
Initial release2015201320152013
Current release5.1, August 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache 2.0Open Source infoSimplified BSD LicenseOpen 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
FreeBSD
Linux
OS X
Linux
Data schemeyespredefined schemeschema-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.nononono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
HTTP RESTMemcached protocolJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresLuanonono
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on CassandranoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infobased on CassandranoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
noneImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID at container level
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnononoAccess rights for users can be defined per database
More information provided by the system vendor
BigObjectBluefloodCachelot.ioGridDB
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
BigObjectBluefloodCachelot.ioGridDB
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