DBMS > Apache Jena - TDB vs. EJDB vs. HugeGraph vs. Milvus

System Properties Comparison Apache Jena - TDB vs. EJDB vs. HugeGraph vs. Milvus

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Editorial information provided by DB-Engines

Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A fast-speed and highly-scalable Graph DBMS

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

Primary database model

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Website

jena.apache.org/documentation/tdb/index.html

github.com/Softmotions/ejdb

github.com/hugegraph
hugegraph.apache.org

milvus.io

Technical documentation

jena.apache.org/documentation/tdb/index.html

github.com/Softmotions/ejdb/blob/master/README.md

hugegraph.apache.org/docs

milvus.io/docs/overview.md

Developer

Apache Software Foundation

originally developed by HP Labs

Softmotions

Baidu

Initial release

2000

2012

2018

2019

Current release

4.9.0, July 2023

0.9

2.3.4, January 2024

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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

Server operating systems

All OS with a Java VM

server-less

Linux
macOS
Unix

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Data scheme

yes

RDF Schemas

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Vector, Numeric and String

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

also supports composite index and range index

SQL

Support of SQL

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

in-process shared library

Java API
RESTful HTTP API
TinkerPop Gremlin

RESTful HTTP API

Supported programming languages

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Groovy
Java
Python

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

Server-side scripts

Stored procedures

yes

asynchronous Gremlin script jobs

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

edges in graph

Transaction concepts

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

ACID

TDB Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Access control via Jena Security

Users, roles and permissions

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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