DBMS > Amazon Redshift vs. Milvus vs. Postgres-XL vs. RocksDB vs. Sadas Engine

System Properties Comparison Amazon Redshift vs. Milvus vs. Postgres-XL vs. RocksDB vs. Sadas Engine

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

milvus.io/docs/overview.md

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Amazon (based on PostgreSQL)

Facebook, Inc.

SADAS s.r.l.

Initial release

2012

2019

2014

since 2012, originally named StormDB

2013

2006

Current release

2.3.4, January 2024

10 R1, October 2018

9.2.1, May 2024

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Mozilla public license

Open Source

BSD

commercial

free trial version 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

C++, Go

C++

Server operating systems

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

Linux

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

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

XML type, but no XML query functionality

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

C++ API
Java API

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

yes

Transaction concepts

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

ACID

MVCC

yes

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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...
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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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