DBMS > Amazon Redshift vs. Milvus vs. Quasardb vs. YugabyteDB

System Properties Comparison Amazon Redshift vs. Milvus vs. Quasardb vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Distributed, high-performance timeseries database

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Secondary database models

Document store
Wide column store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	2.91
Rank	#102	Overall
	#51	Relational DBMS

Website

aws.amazon.com/redshift

milvus.io

quasar.ai

www.yugabyte.com

Technical documentation

docs.aws.amazon.com/redshift

milvus.io/docs/overview.md

doc.quasar.ai/master

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Amazon (based on PostgreSQL)

quasardb

Yugabyte Inc.

Initial release

2012

2019

2009

2017

Current release

2.3.4, January 2024

3.14.1, January 2024

2.19, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache 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

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

C++, Go

C++

C and C++

Server operating systems

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

BSD
Linux
OS X
Windows

Linux
OS X

Data scheme

yes

schema-free

depending on used data model

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes, PostgreSQL compatible

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

HTTP API

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with selectable replication factor

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

based on RocksDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Cryptographically strong user authentication and audit trail

yes

More information provided by the system vendor

Specific characteristics

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

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

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

Systems of record and engagement for cloud native applications that require resilience,...
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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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2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more

Licensing and pricing models

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

Apache 2.0 license for the database
» more

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