DBMS > Apache Pinot vs. Heroic vs. Milvus vs. SpatiaLite

System Properties Comparison Apache Pinot vs. Heroic vs. Milvus vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Spatial extension of SQLite

Primary database model

Secondary database models

Relational DBMS

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	2.78
Rank	#103	Overall
	#3	Vector DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

pinot.apache.org

github.com/spotify/heroic

milvus.io

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.pinot.apache.org

spotify.github.io/heroic

milvus.io/docs/overview.md

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Apache Software Foundation and contributors

Spotify

Alessandro Furieri

Initial release

2015

2014

2019

2008

Current release

1.0.0, September 2023

2.3.4, January 2024

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

C++

Server operating systems

All OS with a Java JDK11 or higher

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

server-less

Data scheme

yes

schema-free

yes

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP API

Supported programming languages

Go
Java
Python

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

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

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

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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

Real-Time Analytics for Mobile App Crashes using Apache Pinot
2 November 2023, Uber

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

Apache Pinot - SD Times Open Source Project of the Week
31 May 2024, SDTimes.com

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

provided by Google News

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31 January 2024, SitePoint

Milvus 2.4 Unveils Game-Changing Features for Enhanced Vector Search
20 March 2024, GlobeNewswire

Zilliz Unveils Game-Changing Features for Vector Search
22 March 2024, Datanami

IBM watsonx.data’s integrated vector database: unify, prepare, and deliver your data for AI
9 April 2024, ibm.com

provided by Google News

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