DBMS > CockroachDB vs. Milvus vs. searchxml vs. SWC-DB

System Properties Comparison CockroachDB vs. Milvus vs. searchxml vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

A DBMS designed for efficient storage of vector data and vector similarity searches

DBMS for structured and unstructured content wrapped with an application server

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Vector DBMS

Native XML DBMS
Search engine

Wide column store

Secondary database models

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.cockroachlabs.com

milvus.io

www.searchxml.net/category/products

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

www.cockroachlabs.com/docs

milvus.io/docs/overview.md

www.searchxml.net/support/handouts

Developer

Cockroach Labs

informationpartners gmbh

Alex Kashirin

Initial release

2015

2019

2015

2020

Current release

23.1.1, May 2023

2.3.4, January 2024

1.0

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

C++, Go

C++

Server operating systems

Linux
macOS
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Windows

Linux

Data scheme

dynamic schema

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like query language

APIs and other access methods

JDBC

RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Proprietary protocol
Thrift

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C++
Go
Java
JavaScript (Node.js)
Python

C++

most other programming languages supported via APIs

C++

Server-side scripts

Stored procedures

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role-based access control

Role based access control and fine grained access rights

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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