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DBMS > GeoMesa vs. Hawkular Metrics vs. NSDb vs. Weaviate

System Properties Comparison GeoMesa vs. Hawkular Metrics vs. NSDb vs. Weaviate

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonNSDb  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelSpatial DBMSTime Series DBMSTime Series DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitewww.geomesa.orgwww.hawkular.orgnsdb.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidensdb.io/­Architectureweaviate.io/­developers/­weaviate
DeveloperCCRi and othersCommunity supported by Red HatWeaviate B.V.
Initial release2014201420172019
Current release4.0.5, February 20241.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache 2.0Open Source infoApache Version 2.0Open Source infocommercial license available with Weaviate Enterprise
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 languageScalaJavaJava, ScalaGo
Server operating systemsLinux
OS X
Windows
Linux
macOS
Data schemeyesschema-freeyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes infostring, int, float, geo point, date, cross reference, fuzzy references
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 indexesyesnoall fields are automatically indexedyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnonoSQL-like query languageGraphQL is used as query language
APIs and other access methodsHTTP RESTgRPC
HTTP REST
WebSocket
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesGo
Java
Python
Ruby
Java
Scala
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnononono
Triggersnoyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layernoyes
User concepts infoAccess controlyes infodepending on the DBMS used for storagenoAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
GeoMesaHawkular MetricsNSDbWeaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
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Key customersAll companies that have data. ​
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Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
GeoMesaHawkular MetricsNSDbWeaviate
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