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DBMS > Databricks vs. Manticore Search vs. Milvus vs. PouchDB

System Properties Comparison Databricks vs. Manticore Search vs. Milvus vs. PouchDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonManticore Search  Xexclude from comparisonMilvus  Xexclude from comparisonPouchDB  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.Multi-storage database for search, including full-text search.A DBMS designed for efficient storage of vector data and vector similarity searchesJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument store
Relational DBMS
Search engineVector DBMSDocument store
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.databricks.commanticoresearch.commilvus.iopouchdb.com
Technical documentationdocs.databricks.commanual.manticoresearch.commilvus.io/­docs/­overview.mdpouchdb.com/­guides
DeveloperDatabricksManticore SoftwareApache Software Foundation
Initial release2013201720192012
Current release6.0, February 20232.4.4, May 20247.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2Open Source infoApache Version 2.0Open Source
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 languageC++C++, GoJavaScript
Server operating systemshostedFreeBSD
Linux
macOS
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeFlexible Schema (defined schema, partial schema, schema free)Fixed schemaschema-free
Typing infopredefined data types such as float or dateInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, BooleanVector, Numeric and Stringno
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.yesCan index from XMLnono
Secondary indexesyesyes infofull-text index on all search fieldsnoyes infovia views
SQL infoSupport of SQLwith Databricks SQLSQL-like query languagenono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesPython
R
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnoView functions in JavaScript
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyesSynchronous replication based on Galera libraryMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infoisolated transactions for atomic changes and binary logging for safe writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnoRole based access control and fine grained access rightsno
More information provided by the system vendor
DatabricksManticore SearchMilvusPouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
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...
» 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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