DBMS > HEAVY.AI vs. InterSystems IRIS vs. Microsoft SQL Server vs. Milvus

System Properties Comparison HEAVY.AI vs. InterSystems IRIS vs. Microsoft SQL Server vs. Milvus

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Microsofts flagship relational DBMS

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

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

www.intersystems.com/products/intersystems-iris

www.microsoft.com/en-us/sql-server

milvus.io

Technical documentation

docs.heavy.ai

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

learn.microsoft.com/en-US/sql/sql-server

milvus.io/docs/overview.md

Developer

HEAVY.AI, Inc.

InterSystems

Microsoft

Initial release

2016

2018

1989

2019

Current release

5.10, January 2022

2023.3, June 2023

SQL Server 2022, November 2022

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

Apache Version 2.0

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++ and CUDA

C++

C++, Go

Server operating systems

Linux

AIX
Linux
macOS
Ubuntu
Windows

Linux
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

yes

depending on used data model

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes, but depending on the SQL-Server Edition

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

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

yes

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

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more

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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