DBMS > Citus vs. FileMaker vs. Milvus
System Properties Comparison Citus vs. FileMaker vs. Milvus
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|Editorial information provided by DB-Engines|
|Name||Citus Xexclude from comparison||FileMaker Xexclude from comparison||Milvus Xexclude from comparison|
|Description||Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL||FileMaker is a cross-platform RDBMS that includes a GUI frontend.||A DBMS designed for efficient storage of vector data and vector similarity searches|
|Primary database model||Relational DBMS||Relational DBMS||Vector DBMS|
|Secondary database models||Document store|
|Developer||FileMaker a subsidiary of Apple|
|Current release||8.1, December 2018||19.4.1, November 2021||2.2, November 2022|
|License Commercial or Open Source||Open Source AGPL, commercial license also available||commercial||Open Source Apache Version 2.0|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Zilliz Cloud – Cloud-native service for Milvus|
|Implementation language||C||C++, Go|
|Server operating systems||Linux||iOS client part only|
macOS 10.14 or later
Windows with WSL 2 enabled
|Typing predefined data types such as float or date||yes||yes||Vector, Numeric and String|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||yes specific XML type available, but no XML query functionality||yes A http query request can return the data in XML format||no|
|SQL Support of SQL||yes standard, with numerous extensions||yes via plugins||no|
|APIs and other access methods||ADO.NET|
native C library
streaming API for large objects
|RESTful HTTP API|
|Supported programming languages||.Net|
|Server-side scripts Stored procedures||user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.||yes||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||none||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||Source-replica replication other methods possible by using 3rd party extensions||Source-replica replication, warm standby since Version 14|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Bounded Staleness|
|Foreign keys Referential integrity||yes||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||no||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no||no|
|User concepts Access control||fine grained access rights according to SQL-standard||simple rights management via user accounts and connection to external directory services||no|
|More information provided by the system vendor|
|Specific characteristics||Milvus is an open-source and cloud-native vector database built for production-ready...|
|Competitive advantages||Highly available, versatile, and robust with millisecond latency. Supports batch...|
|Typical application scenarios||Video media : video understanding, video deduplication. E-commerce and mobile applications...|
|Key customers||Milvus is trusted by over 1,000 enterprises, including Baidu, eBay, IKEA, LINE, Shopee,...|
|Market metrics||As of February 2023, 14k+ GitHub stars 2M+ downloads and installations 1000+ enterprise...|
|Licensing and pricing models||Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...|
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