DBMS > Graph Engine vs. IBM Cloudant vs. Milvus vs. OpenSearch

System Properties Comparison Graph Engine vs. IBM Cloudant vs. Milvus vs. OpenSearch

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Database as a Service offering based on Apache CouchDB

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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Graph DBMS
Key-value store

Document store

Vector DBMS

Search engine

Secondary database models

Vector DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Website

www.graphengine.io

www.ibm.com/products/cloudant

milvus.io

github.com/opensearch-project
opensearch.org

Technical documentation

www.graphengine.io/docs/manual

cloud.ibm.com/docs/Cloudant

milvus.io/docs/overview.md

opensearch.org/docs/latest

Developer

Microsoft

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Amazon Web Services

Initial release

2010

2019

2021

Current release

2.3.4, January 2024

2.5.0, January 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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

Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.
STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.

Implementation language

.NET and C

Erlang

C++, Go

Java

Server operating systems

.NET

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

All OS with a Java VM

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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.

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
C++
F#
Visual Basic

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

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

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» 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...
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Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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The OpenSearch Project offers open source software licensed under Apache License...
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