DBMS > Ehcache vs. JanusGraph vs. Milvus vs. Newts vs. Valentina Server

System Properties Comparison Ehcache vs. JanusGraph vs. Milvus vs. Newts vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Time Series DBMS based on Cassandra

Object-relational database and reports server

Primary database model

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

www.ehcache.org

janusgraph.org

milvus.io

opennms.github.io/newts

www.valentina-db.net

Technical documentation

www.ehcache.org/documentation

docs.janusgraph.org

milvus.io/docs/overview.md

github.com/OpenNMS/newts/wiki

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Terracotta Inc, owned by Software AG

Linux Foundation; originally developed as Titan by Aurelius

OpenNMS Group

Paradigma Software

Initial release

2009

2017

2019

2014

1999

Current release

3.10.0, March 2022

0.6.3, February 2023

2.3.4, January 2024

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

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

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

Data scheme

schema-free

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

SQL

Support of SQL

yes

APIs and other access methods

JCache

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

HTTP REST
Java API

ODBC

Supported programming languages

Java

Clojure
Java
Python

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

Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency
Immediate Consistency

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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.

Related products and services

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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