DBMS > BigObject vs. HyperSQL vs. Milvus vs. OpenSearch

System Properties Comparison BigObject vs. HyperSQL vs. Milvus vs. OpenSearch

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Vector DBMS

Search engine

Secondary database models

Vector DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Website

bigobject.io

hsqldb.org

milvus.io

github.com/opensearch-project
opensearch.org

Technical documentation

docs.bigobject.io

hsqldb.org/web/hsqlDocsFrame.html

milvus.io/docs/overview.md

opensearch.org/docs/latest

Developer

BigObject, Inc.

Amazon Web Services

Initial release

2015

2001

2019

2021

Current release

2.7.2, June 2023

2.4.4, May 2024

2.5.0, January 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

based on BSD license

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

STACKIT OpenSearch offers OpenSearch in a managed version in enterprise grade, 100% GDPR-compliant, for a wide range of applications like analytics, website search, offering scalability and fast data access.
Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.

Implementation language

Java

C++, Go

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

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

All OS with a Java VM

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

Typing

predefined data types such as float or date

yes

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

All search fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC
Java

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Server-side scripts

Stored procedures

Lua

Java, SQL

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

More information provided by the system vendor

Specific characteristics

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

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

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

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

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

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» 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

The OpenSearch Project offers open source software licensed under Apache License...
» more

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