DBMS > Cubrid vs. Drizzle vs. Linter vs. Milvus vs. Rockset

System Properties Comparison Cubrid vs. Drizzle vs. Linter vs. Milvus vs. Rockset

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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

RDBMS for high security requirements

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Vector DBMS

Document store

Secondary database models

Spatial DBMS

Relational DBMS
Search engine

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

cubrid.com (korean)
cubrid.org (english)

linter.ru

milvus.io

rockset.com

Technical documentation

cubrid.org/manuals

milvus.io/docs/overview.md

docs.rockset.com

Developer

CUBRID Corporation, CUBRID Foundation

Drizzle project, originally started by Brian Aker

relex.ru

Rockset

Initial release

2008

1990

2019

Current release

11.0, January 2021

7.2.4, September 2012

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

Open Source

Apache Version 2.0

commercial

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++, Java

C++

C and C++

C++, Go

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

yes

Read-only SQL queries, including JOINs

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

RESTful HTTP API

HTTP REST

Supported programming languages

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

C
C++
Java
PHP

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

yes

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

Access rights for users and organizations can be defined via Rockset console

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

show all

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

NHN Willing to Be More Open
24 November 2008, 코리아타임스

provided by Google 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
31 January 2024, SitePoint

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

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

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

provided by Google News

Rockset Announces Native Support for Hybrid Search to Power AI Apps
17 May 2024, Datanami

Rockset upgrades database to meet the needs of AI hybrid search – Blocks and Files
20 May 2024, Blocks & Files

Data Management News for the Week of May 17; Updates from Anomalo, DataStax, Rockset & More
16 May 2024, Solutions Review

Rockset launches native support for hybrid vector and text search to power AI apps
16 May 2024, SiliconANGLE News

Rockset targets cost control with latest database update
31 January 2024, TechTarget

provided by Google News

Share this page