DBMS > HyperSQL vs. InfinityDB vs. Milvus vs. NSDb

System Properties Comparison HyperSQL vs. InfinityDB vs. Milvus vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A Java embedded Key-Value Store which extends the Java Map interface

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

Primary database model

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

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

boilerbay.com/infinitydb/manual

milvus.io/docs/overview.md

nsdb.io/Architecture

Developer

Boiler Bay Inc.

Initial release

2001

2002

2019

2017

Current release

2.7.2, June 2023

4.0

2.3.4, January 2024

License

Commercial or Open Source

Open Source

based on BSD license

commercial

Open Source

Apache Version 2.0

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

Java

C++, Go

Java, Scala

Server operating systems

All OS with a Java VM

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

All OS with a Java VM

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
macOS

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

Vector, Numeric and String

yes: int, bigint, decimal, 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.

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC
Java

Java

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

Java
Scala

Server-side scripts

Stored procedures

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

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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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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