DBMS > Databend vs. IBM Cloudant vs. Milvus vs. RocksDB

System Properties Comparison Databend vs. IBM Cloudant vs. Milvus vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Database as a Service offering based on Apache CouchDB

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

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

Score	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

github.com/datafuselabs/databend
www.databend.com

www.ibm.com/products/cloudant

milvus.io

rocksdb.org

Technical documentation

docs.databend.com

cloud.ibm.com/docs/Cloudant

milvus.io/docs/overview.md

github.com/facebook/rocksdb/wiki

Developer

Databend Labs

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Facebook, Inc.

Initial release

2021

2010

2019

2013

Current release

1.0.59, April 2023

2.3.4, January 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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

Rust

Erlang

C++, Go

C++

Server operating systems

hosted
Linux
macOS

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP/JSON API

RESTful HTTP API

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

atomic operations within a document possible

yes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Users with fine-grained authorization concept, user roles

Access rights for users can be defined per database

Role based access control and fine grained access rights

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...
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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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