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DBMS > Databricks vs. Hawkular Metrics vs. Milvus vs. Postgres-XL

System Properties Comparison Databricks vs. Hawkular Metrics vs. Milvus vs. Postgres-XL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Hawkular 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 searchesBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Relational DBMS
Time Series DBMSVector DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitewww.databricks.comwww.hawkular.orgmilvus.iowww.postgres-xl.org
Technical documentationdocs.databricks.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mdwww.postgres-xl.org/­documentation
DeveloperDatabricksCommunity supported by Red Hat
Initial release2013201420192014 infosince 2012, originally named StormDB
Current release2.4.4, May 202410 R1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageJavaC++, GoC
Server operating systemshostedLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyes
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.yesnonoyes infoXML type, but no XML query functionality
Secondary indexesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLnonoyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
Go
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonouser defined functions
Triggersyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoMVCC
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.nonoyesno
User concepts infoAccess controlnoRole based access control and fine grained access rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHawkular MetricsMilvusPostgres-XL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Milvus 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...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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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
DatabricksHawkular MetricsMilvusPostgres-XL
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