DBMS > Hypertable vs. Milvus vs. OpenSearch vs. Sphinx

System Properties Comparison Hypertable vs. Milvus vs. OpenSearch vs. Sphinx

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Wide column store

Vector DBMS

Search engine

Secondary database models

Vector DBMS

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

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

milvus.io

github.com/opensearch-project
opensearch.org

sphinxsearch.com

Technical documentation

milvus.io/docs/overview.md

opensearch.org/docs/latest

sphinxsearch.com/docs

Developer

Hypertable Inc.

Amazon Web Services

Sphinx Technologies Inc.

Initial release

2009

2019

2021

2001

Current release

0.9.8.11, March 2016

2.3.4, January 2024

2.5.0, January 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence 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.

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Implementation language

C++

C++, Go

Java

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

All OS with a Java VM

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

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

restricted

only exact value or prefix value scans

yes

All search fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

C++ API
Thrift

RESTful HTTP API

Java API
RESTful HTTP/JSON API

Proprietary protocol

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes

none

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

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

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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...
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Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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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...
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Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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The OpenSearch Project offers open source software licensed under Apache License...
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