DBMS > Hive vs. Milvus vs. Oracle vs. OrientDB

System Properties Comparison Hive vs. Milvus vs. Oracle vs. OrientDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Widely used RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

hive.apache.org

milvus.io

www.oracle.com/database

orientdb.org

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

milvus.io/docs/overview.md

docs.oracle.com/en/database

www.orientdb.com/docs/last/index.html

Developer

Apache Software Foundation

initially developed by Facebook

Oracle

OrientDB LTD; CallidusCloud; SAP

Initial release

2012

2019

1980

2010

Current release

3.1.3, April 2022

2.3.4, January 2024

23c, September 2023

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Apache version 2

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

C and C++

Java

Server operating systems

All OS with a Java VM

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC
Thrift

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C++
Java
PHP
Python

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

PL/SQL

also stored procedures in Java possible

Java, Javascript

Triggers

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

can be realized in PL/SQL

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users, groups and roles

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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.