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DBMS > Coveo vs. Google Cloud Firestore vs. GridDB vs. HBase

System Properties Comparison Coveo vs. Google Cloud Firestore vs. GridDB vs. HBase

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGridDB  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Scalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelSearch engineDocument storeTime Series DBMSWide column store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.28
Rank#114  Overall
#11  Search engines
Score7.85
Rank#51  Overall
#8  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitewww.coveo.comfirebase.google.com/­products/­firestoregriddb.nethbase.apache.org
Technical documentationdocs.coveo.comfirebase.google.com/­docs/­firestoredocs.griddb.nethbase.apache.org/­book.html
DeveloperCoveoGoogleToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2012201720132008
Current release5.1, August 20222.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedhostedLinuxLinux
Unix
Windows infousing Cygwin
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVRO
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 indexesyesyesyesno
SQL infoSupport of SQLnonoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsRESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Supported programming languagesC#
Java
JavaScript
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsnoyes infoCoprocessors in Java
Triggersyesyes, with Cloud Functionsyesyes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesACID at container levelSingle row ACID (across millions of columns)
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.yesyes
User concepts infoAccess controlgranular access controls, API key management, content filtersAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
CoveoGoogle Cloud FirestoreGridDBHBase
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
CoveoGoogle Cloud FirestoreGridDBHBase
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