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DBMS > GridDB vs. Hive vs. Manticore Search vs. VictoriaMetrics

System Properties Comparison GridDB vs. Hive vs. Manticore Search vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHive  Xexclude from comparisonManticore Search  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big Datadata warehouse software for querying and managing large distributed datasets, built on HadoopMulti-storage database for search, including full-text search.A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelTime Series DBMSRelational DBMSSearch engineTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websitegriddb.nethive.apache.orgmanticoresearch.comvictoriametrics.com
Technical documentationdocs.griddb.netcwiki.apache.org/­confluence/­display/­Hive/­Homemanual.manticoresearch.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperToshiba CorporationApache Software Foundation infoinitially developed by FacebookManticore SoftwareVictoriaMetrics
Initial release2013201220172018
Current release5.1, August 20223.1.3, April 20226.0, February 2023v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open Source infoGPL version 2Open Source infoApache Version 2.0
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 languageC++JavaC++Go
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
macOS
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesyesFixed schema
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.noCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functionsno
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorSynchronous replication based on Galera librarySynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and rolesno
More information provided by the system vendor
GridDBHiveManticore SearchVictoriaMetrics
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
GridDBHiveManticore SearchVictoriaMetrics
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