DBMS > HyperSQL vs. Milvus vs. NCache vs. RavenDB

System Properties Comparison HyperSQL vs. Milvus vs. NCache vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Open-Source and Enterprise in-memory Key-Value Store

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

hsqldb.org

milvus.io

www.alachisoft.com/ncache

ravendb.net

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

milvus.io/docs/overview.md

www.alachisoft.com/resources/docs

ravendb.net/docs

Developer

Alachisoft

Hibernating Rhinos

Initial release

2001

2019

2005

2010

Current release

2.7.2, June 2023

2.3.4, January 2024

5.3.3, April 2024

5.4, July 2022

License

Commercial or Open Source

Open Source

based on BSD license

Open Source

Apache Version 2.0

Open Source

Enterprise Edition available

Open Source

AGPL version 3, commercial license available

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#, .NET, .NET Core, Java

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

SQL-like query language (RQL)

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC
Java

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

Java, SQL

support for stored procedures with SQL-Server CLR

yes

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID, Cluster-wide transaction available

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

Role based access control and fine grained access rights

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Authorization levels configured per client per database

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
» more

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
» more

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
» more

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» 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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