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DBMS > Databend vs. Datomic vs. Milvus vs. Solr

System Properties Comparison Databend vs. Datomic vs. Milvus vs. Solr

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonDatomic  Xexclude from comparisonMilvus  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA DBMS designed for efficient storage of vector data and vector similarity searchesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSVector DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.datomic.commilvus.iosolr.apache.org
Technical documentationdocs.databend.comdocs.datomic.commilvus.io/­docs/­overview.mdsolr.apache.org/­resources.html
DeveloperDatabend LabsCognitectApache Software Foundation
Initial release2021201220192006
Current release1.0.59, April 20231.0.7075, December 20232.4.4, May 20249.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoApache Version 2.0Open Source infoApache 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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageRustJava, ClojureC++, GoJava
Server operating systemshosted
Linux
macOS
All OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesnoyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnonoSolr Parallel SQL Interface
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
RESTful HTTP APIRESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
Clojure
Java
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction FunctionsnoJava plugins
TriggersnoBy using transaction functionsnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone infoBut extensive use of caching in the application peersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnoRole based access control and fine grained access rightsyes
More information provided by the system vendor
DatabendDatomicMilvusSolr
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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DatabendDatomicMilvusSolr
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