DBMS > Amazon Redshift vs. GBase vs. Graph Engine vs. Milvus vs. SQLite

System Properties Comparison Amazon Redshift vs. GBase vs. Graph Engine vs. Milvus vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Vector DBMS

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

milvus.io/docs/overview.md

www.sqlite.org/docs.html

Developer

Amazon (based on PostgreSQL)

General Data Technology Co., Ltd.

Microsoft

Dwayne Richard Hipp

Initial release

2012

2004

2010

2019

2000

Current release

GBase 8a, GBase 8s, GBase 8c

2.4.4, May 2024

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

Public Domain

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, Java, Python

.NET and C

C++, Go

Server operating systems

hosted

Linux

.NET

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Standard with numerous extensions

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

horizontal partitioning

Sharding

none

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

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

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

yes

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...
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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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