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DBMS > GridDB vs. Hawkular Metrics vs. Milvus vs. OpenTSDB

System Properties Comparison GridDB vs. Hawkular Metrics vs. Milvus vs. OpenTSDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonOpenTSDB  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.A DBMS designed for efficient storage of vector data and vector similarity searchesScalable Time Series DBMS based on HBase
Primary database modelTime Series DBMSTime Series DBMSVector DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.68
Rank#146  Overall
#12  Time Series DBMS
Websitegriddb.netwww.hawkular.orgmilvus.ioopentsdb.net
Technical documentationdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mdopentsdb.net/­docs/­build/­html/­index.html
DeveloperToshiba CorporationCommunity supported by Red Hatcurrently maintained by Yahoo and other contributors
Initial release2013201420192011
Current release5.1, August 20222.3.4, January 2024
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 infoApache Version 2.0Open Source infoLGPL
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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++JavaC++, GoJava
Server operating systemsLinuxLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Windows
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesVector, Numeric and Stringnumeric data for metrics, strings for tags
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 indexesyesnonono
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)nonono
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTRESTful HTTP APIHTTP API
Telnet API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Erlang
Go
Java
Python
R
Ruby
Server-side scripts infoStored proceduresnononono
Triggersyesyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on Cassandraselectable replication factor infobased on HBase
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
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonono
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.yesnoyesno
User concepts infoAccess controlAccess rights for users can be defined per databasenoRole based access control and fine grained access rightsno
More information provided by the system vendor
GridDBHawkular MetricsMilvusOpenTSDB
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
GridDBHawkular MetricsMilvusOpenTSDB
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