DBMS > FeatureBase vs. Microsoft Azure SQL Database vs. Milvus vs. NSDb vs. OrigoDB

System Properties Comparison FeatureBase vs. Microsoft Azure SQL Database vs. Milvus vs. NSDb vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Vector DBMS

Time Series DBMS

Document store
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

www.featurebase.com

azure.microsoft.com/en-us/products/azure-sql/database

milvus.io

nsdb.io

origodb.com

Technical documentation

docs.featurebase.com

docs.microsoft.com/en-us/azure/azure-sql

milvus.io/docs/overview.md

nsdb.io/Architecture

origodb.com/docs

Developer

Molecula and Pilosa Open Source Contributors

Microsoft

Robert Friberg et al

Initial release

2017

2010

2019

2017

2009

under the name LiveDB

Current release

2022, May 2022

V12

2.3.4, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

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++, Go

Java, Scala

Server operating systems

Linux
macOS

hosted

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes: int, bigint, decimal, string

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL queries

yes

SQL-like query language

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

ADO.NET
JDBC
ODBC

RESTful HTTP API

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

Java
Python

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

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

Java
Scala

.Net

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

Source-replica replication

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

depending on model

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

Using Apache Lucene

yes

Write ahead log

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

Role based access control and fine grained access rights

Role based authorization

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

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More resources

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4 January 2021, Paul Andlinger, Matthias Gelbmann

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Recent citations in the news

The 10 Hottest Big Data Startups Of 2021
18 November 2021, CRN

Get Your Infrastructure Ready for Real-Time Analytics
8 March 2022, Built In

Funding wrap: H.O. Maycotte's Molecula raises $10M, rebrands; UT snags $15M to lead regional innovation hub
12 September 2022, The Business Journals

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28 September 2021, Business Insider

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11 January 2024, Oracle

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25 April 2024, Microsoft

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26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

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20 March 2024, GlobeNewswire

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22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
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provided by Google News

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