DBMS > Hive vs. InfinityDB vs. Milvus vs. TerminusDB

System Properties Comparison Hive vs. InfinityDB vs. Milvus vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A Java embedded Key-Value Store which extends the Java Map interface

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store
RDF store

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

boilerbay.com/infinitydb/manual

milvus.io/docs/overview.md

terminusdb.github.io/terminusdb/#

Developer

Apache Software Foundation

initially developed by Facebook

Boiler Bay Inc.

DataChemist Ltd.

Initial release

2012

2002

2019

2018

Current release

3.1.3, April 2022

4.0

2.3.4, January 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

All OS with a Java VM

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC
Thrift

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C++
Java
PHP
Python

Java

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

Role based access control and fine grained access rights

Role-based access control

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

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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Vector databases
2 June 2023, Matthias Gelbmann

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