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DBMS > GridDB vs. Hawkular Metrics vs. JaguarDB vs. Manticore Search

System Properties Comparison GridDB vs. Hawkular Metrics vs. JaguarDB vs. Manticore Search

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonJaguarDB  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Performant, highly scalable DBMS for AI and IoT applicationsMulti-storage database for search, including full-text search.
Primary database modelTime Series DBMSTime Series DBMSKey-value store
Vector DBMS
Search engine
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
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.06
Rank#381  Overall
#59  Key-value stores
#15  Vector DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Websitegriddb.netwww.hawkular.orgwww.jaguardb.commanticoresearch.com
Technical documentationdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.jaguardb.com/­support.htmlmanual.manticoresearch.com
DeveloperToshiba CorporationCommunity supported by Red HatDataJaguar, Inc.Manticore Software
Initial release2013201420152017
Current release5.1, August 20223.3 July 20236.0, February 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 2.0Open Source infoGPL V3.0Open Source infoGPL version 2
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++ infothe server part. Clients available in other languagesC++
Server operating systemsLinuxLinux
OS X
Windows
LinuxFreeBSD
Linux
macOS
Windows
Data schemeyesschema-freeyesFixed schema
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesInt, 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.nononoCan index from XML
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like query language
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnononouser defined functions
Triggersyesyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on CassandraMulti-source replicationSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonoyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users can be defined per databasenorights management via user accountsno
More information provided by the system vendor
GridDBHawkular MetricsJaguarDBManticore Search
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
GridDBHawkular MetricsJaguarDBManticore Search
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