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DBMS > Coveo vs. GridDB vs. HBase vs. Milvus

System Properties Comparison Coveo vs. GridDB vs. HBase vs. Milvus

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonGridDB  Xexclude from comparisonHBase  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAI-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 DataWide-column store based on Apache Hadoop and on concepts of BigTableA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelSearch engineTime Series DBMSWide column storeVector DBMS
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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitewww.coveo.comgriddb.nethbase.apache.orgmilvus.io
Technical documentationdocs.coveo.comdocs.griddb.nethbase.apache.org/­book.htmlmilvus.io/­docs/­overview.md
DeveloperCoveoToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2012201320082019
Current release5.1, August 20222.3.4, January 20212.3.4, January 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 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++JavaC++, Go
Server operating systemshostedLinuxLinux
Unix
Windows infousing Cygwin
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROVector, Numeric and String
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 indexesyesyesnono
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
RESTful HTTP API
Supported programming languagesC#
Java
JavaScript
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyes infoCoprocessors in Javano
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelSingle row ACID (across millions of columns)no
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 controlgranular access controls, API key management, content filtersAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole based access control and fine grained access rights
More information provided by the system vendor
CoveoGridDBHBaseMilvus
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsGitHub trending repository
» more
As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
CoveoGridDBHBaseMilvus
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