DBMS > OpenSearch vs. Pinecone vs. Qdrant

System Properties Comparison OpenSearch vs. Pinecone vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

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

A managed, cloud-native vector database

A high-performance vector database with neural network or semantic-based matching

Primary database model

Search engine

Vector DBMS

Secondary database models

Vector DBMS

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

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

github.com/opensearch-project
opensearch.org

www.pinecone.io

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

opensearch.org/docs/latest

docs.pinecone.io/docs/overview

qdrant.tech/documentation

Developer

Amazon Web Services

Pinecone Systems, Inc

Qdrant

Initial release

2021

2019

2021

Current release

2.5.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

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.

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

Rust

Server operating systems

All OS with a Java VM

hosted

Docker
Linux
macOS
Windows

Data scheme

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

Numbers, Strings, Geo, Boolean

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

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP/JSON API

RESTful HTTP API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

Eventual Consistency, tunable consistency

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

In-memory capabilities

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

yes

User concepts

Access control

Key-based authentication

More information provided by the system vendor

Specific characteristics

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

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

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

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