DBMS > Amazon Redshift vs. Graph Engine vs. Milvus vs. YDB

System Properties Comparison Amazon Redshift vs. Graph Engine vs. Milvus vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

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

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Vector DBMS

Document store
Relational DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.81
Rank	#144	Overall
	#5	Vector DBMS

Score	0.34
Rank	#285	Overall
	#43	Document stores
	#130	Relational DBMS

Website

aws.amazon.com/redshift

www.graphengine.io

milvus.io

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

milvus.io/docs/overview.md

ydb.tech/en/docs

Developer

Amazon (based on PostgreSQL)

Microsoft

Yandex

Initial release

2012

2010

2019

Current release

2.3.4, January 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

Apache 2.0; commercial license available

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

.NET and C

C++, Go

Server operating systems

hosted

.NET

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

Data scheme

yes

Flexible Schema (defined schema, partial 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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

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

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-passive shard replication

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

informational only, not enforced by the system

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Access rights defined for Yandex Cloud users

More information provided by the system vendor

Specific characteristics

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

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