DBMS > Drizzle vs. GBase vs. Milvus vs. Transbase

System Properties Comparison Drizzle vs. GBase vs. Milvus vs. Transbase

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

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

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	3.01
Rank	#89	Overall
	#4	Vector DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

www.gbase.cn

milvus.io

www.transaction.de/en/products/transbase.html

Technical documentation

milvus.io/docs/overview.md

www.transaction.de/en/products/transbase/features.html

Developer

Drizzle project, originally started by Brian Aker

General Data Technology Co., Ltd.

Transaction Software GmbH

Initial release

2008

2004

2019

1987

Current release

7.2.4, September 2012

GBase 8a, GBase 8s, GBase 8c

2.4.4, May 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache Version 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

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, Java, Python

C++, Go

C and C++

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

Standard with numerous extensions

yes

APIs and other access methods

JDBC

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Java
PHP

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

Role based access control and fine grained access rights

fine grained access rights 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...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

Typical application scenarios

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

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...
» more

Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr - SitePoint
30 August 2024, SitePoint

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, IBM

10 top vector database options for similarity searches
8 August 2024, TechTarget

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

provided by Google News

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