DBMS > Apache Drill vs. H2 vs. Milvus vs. Oracle Rdb

System Properties Comparison Apache Drill vs. H2 vs. Milvus vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

drill.apache.org

www.h2database.com

milvus.io

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

drill.apache.org/docs

www.h2database.com/html/main.html

milvus.io/docs/overview.md

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Apache Software Foundation

Thomas Mueller

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2012

2005

2019

1984

Current release

1.20.3, January 2023

2.2.220, July 2023

2.3.4, January 2024

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2.0

commercial

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

Java

C++, Go

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

HP Open VMS

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

C++

Java

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

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

With clustering: 2 database servers on different computers operate on identical copies of a database

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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, on a single node

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

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...
» 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

Vector databases
2 June 2023, Matthias Gelbmann

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