DBMS > Amazon Redshift vs. BigObject vs. Brytlyt vs. Milvus

System Properties Comparison Amazon Redshift vs. BigObject vs. Brytlyt vs. Milvus

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for real-time computations and queries

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Vector DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

aws.amazon.com/redshift

bigobject.io

brytlyt.io

milvus.io

Technical documentation

docs.aws.amazon.com/redshift

docs.bigobject.io

docs.brytlyt.io

milvus.io/docs/overview.md

Developer

Amazon (based on PostgreSQL)

BigObject, Inc.

Brytlyt

Initial release

2012

2015

2016

2019

Current release

5.0, August 2023

2.3.4, January 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

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

Implementation language

C, C++ and CUDA

C++, Go

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

yes

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

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

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

user defined functions

in PL/pgSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

fine grained access rights according to SQL-standard

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....
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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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