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DBMS > GeoSpock vs. Hawkular Metrics vs. Milvus vs. PostGIS vs. XTDB

System Properties Comparison GeoSpock vs. Hawkular Metrics vs. Milvus vs. PostGIS vs. XTDB

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonPostGIS  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleHawkular 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 searchesSpatial extension of PostgreSQLA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSTime Series DBMSVector DBMSSpatial DBMSDocument store
Secondary database modelsTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitegeospock.comwww.hawkular.orgmilvus.iopostgis.netgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mdpostgis.net/­documentationwww.xtdb.com/­docs
DeveloperGeoSpockCommunity supported by Red HatJuxt Ltd.
Initial release2014201920052019
Current release2.0, September 20192.3.4, January 20243.4.2, February 20241.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoGPL v2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnononono
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 languageJava, JavascriptJavaC++, GoCClojure
Server operating systemshostedLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyesyes, extensible-data-notation format
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.nononoyesno
Secondary indexestemporal, categoricalnonoyesyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)nonoyeslimited SQL, making use of Apache Calcite
APIs and other access methodsJDBCHTTP RESTRESTful HTTP APIHTTP REST
JDBC
Supported programming languagesGo
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Clojure
Java
Server-side scripts infoStored proceduresnononouser defined functionsno
Triggersnoyes infovia Hawkular Alertingnoyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infobased on CassandraShardingyes infobased on PostgreSQLnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes infobased on PostgreSQLyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users can be defined per tablenoRole based access control and fine grained access rightsyes infobased on PostgreSQL
More information provided by the system vendor
GeoSpockHawkular MetricsMilvusPostGISXTDB infoformerly named Crux
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
GeoSpockHawkular MetricsMilvusPostGISXTDB infoformerly named Crux
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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