DBMS > Linter vs. Milvus vs. QuestDB
System Properties Comparison Linter vs. Milvus vs. QuestDB
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|Editorial information provided by DB-Engines|
|Name||Linter Xexclude from comparison||Milvus Xexclude from comparison||QuestDB Xexclude from comparison|
|Description||RDBMS for high security requirements||A DBMS designed for efficient storage of vector data and vector similarity searches||A high performance open source SQL database for time series data|
|Primary database model||Relational DBMS||Search engine||Time Series DBMS|
|Secondary database models||Spatial DBMS||Relational DBMS|
|Current release||2.2, November 2022|
|License Commercial or Open Source||commercial||Open Source Apache Version 2.0||Open Source Apache 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 and C++||C++, Go||Java|
|Server operating systems||AIX|
HP Open VMS
macOS 10.14 or later
Windows with WSL 2 enabled
|Data scheme||yes||yes schema-free via InfluxDB Line Protocol|
|Typing predefined data types such as float or date||yes||Vector, Numeric and String||yes|
|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.||no||no||no|
|SQL Support of SQL||yes||no||SQL-like query language|
|APIs and other access methods||ADO.NET|
Oracle Call Interface (OCI)
|RESTful HTTP API||HTTP REST|
InfluxDB Line Protocol (TCP/UDP)
|Supported programming languages||C|
|C PostgreSQL driver|
Rust over HTTP
|Server-side scripts Stored procedures||yes proprietary syntax with the possibility to convert from PL/SQL||no||no|
|Partitioning methods Methods for storing different data on different nodes||none||Sharding||horizontal partitioning (by timestamps)|
|Replication methods Methods for redundantly storing data on multiple nodes||Source-replica replication||Configurable consistency for N replicas|
|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||no||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||no||ACID for single-table writes|
|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||yes through memory mapped files|
|User concepts Access control||fine grained access rights according to SQL-standard||no|
|More information provided by the system vendor|
|Specific characteristics||Milvus is an open-source and cloud-native vector database built for production-ready...|
|Relational model with native time series support Column based storage and time partitioned...|
|Competitive advantages||Highly available, versatile, and robust with millisecond latency. Supports batch...|
|Real-time data ingestion and istant SQL queries for time series High performance...|
|Typical application scenarios||Video media : video understanding, video deduplication. E-commerce and mobile applications...|
|Application metrics Financial market data and algo trading DevOps monitoring Real-time...|
|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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