DBMS > HyperSQL vs. OpenSearch vs. Pinecone

System Properties Comparison HyperSQL vs. OpenSearch vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

A managed, cloud-native vector database

Primary database model

Relational DBMS

Search engine

Vector DBMS

Secondary database models

Vector DBMS

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

Score	4.91
Rank	#82	Overall
	#43	Relational DBMS

Score	12.61
Rank	#46	Overall
	#4	Search engines

Score	3.01
Rank	#113	Overall
	#2	Vector DBMS

Website

hsqldb.org

github.com/opensearch-project
opensearch.org

www.pinecone.io

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

opensearch.org/docs/latest

docs.pinecone.io/docs/overview

Developer

Amazon Web Services

Pinecone Systems, Inc

Initial release

2001

2021

2019

Current release

2.7.1, October 2022

2.5.0, January 2023

License

Commercial or Open Source

Open Source

based on BSD license

Open Source

Apache Version 2.0

commercial

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 including search engine, NoSQL document database, and visualization interface.

Implementation language

Java

Server operating systems

All OS with a Java VM

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

All OS with a Java VM

hosted

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

String, Number, 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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC
Java

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

Python

Server-side scripts

Stored procedures

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

Immediate 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

Transaction concepts

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

ACID

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

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

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

Typical application scenarios

OpenSearch is used across a broad range of search, analytics, and observability applications....
» more

Licensing and pricing models

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

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