DBMS > Milvus vs. MonetDB vs. Sadas Engine vs. TimesTen

System Properties Comparison Milvus vs. MonetDB vs. Sadas Engine vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

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

A relational database management system that stores data in columns

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

In-Memory RDBMS compatible to Oracle

Primary database model

Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

milvus.io

www.monetdb.org

www.sadasengine.com

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

Technical documentation

milvus.io/docs/overview.md

www.monetdb.org/Documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.oracle.com/database/timesten-18.1

Developer

MonetDB BV

SADAS s.r.l.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2019

2004

2006

1998

Current release

2.3.4, January 2024

Dec2023 (11.49), December 2023

8.0

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Mozilla Public License 2.0

commercial

free trial version available

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

C++, Go

C++

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

FreeBSD
Linux
OS X
Solaris
Windows

AIX
Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

SQL 2003 with some extensions

yes

APIs and other access methods

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes, in SQL, C, R

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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

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2 June 2023, Matthias Gelbmann

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