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DBMS > atoti vs. BigObject vs. Coveo vs. GridDB

System Properties Comparison atoti vs. BigObject vs. Coveo vs. GridDB

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonBigObject  Xexclude from comparisonCoveo  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Analytic DBMS for real-time computations and queriesAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentScalable in-memory time series database optimized for IoT and Big Data
Primary database modelObject oriented DBMSRelational DBMS infoa hierachical model (tree) can be imposedSearch engineTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score2.28
Rank#114  Overall
#11  Search engines
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websiteatoti.iobigobject.iowww.coveo.comgriddb.net
Technical documentationdocs.atoti.iodocs.bigobject.iodocs.coveo.comdocs.griddb.net
DeveloperActiveViamBigObject, Inc.CoveoToshiba Corporation
Initial release201520122013
Current release5.1, August 2022
License infoCommercial or Open Sourcecommercial infofree versions availablecommercial infofree community edition availablecommercialOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hostedLinux
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyes
Typing infopredefined data types such as float or dateyesyesyes 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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like DML and DDL statementsnoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC#
Java
JavaScript
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresPythonLuanono
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesSource-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 systemnoneImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID at container level
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes infoRead/write lock on objects (tables, trees)yesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlnogranular access controls, API key management, content filtersAccess rights for users can be defined per database
More information provided by the system vendor
atotiBigObjectCoveoGridDB
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
atotiBigObjectCoveoGridDB
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