DBMS > Geode vs. Milvus vs. Valentina Server vs. XTDB

System Properties Comparison Geode vs. Milvus vs. Valentina Server vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Object-relational database and reports server

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

geode.apache.org

milvus.io

www.valentina-db.net

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

geode.apache.org/docs

milvus.io/docs/overview.md

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

www.xtdb.com/docs

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Paradigma Software

Juxt Ltd.

Initial release

2002

2019

1999

2019

Current release

1.1, February 2017

2.3.4, January 2024

5.7.5

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2.0

commercial

Open Source

MIT License

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

Clojure

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

yes

yes, extensible-data-notation format

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

SQL-like query language (OQL)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

RESTful HTTP API

ODBC

HTTP REST
JDBC

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

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

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

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 per client and object definable

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.

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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