DBMS > Graphite vs. Milvus vs. ObjectBox vs. Snowflake

System Properties Comparison Graphite vs. Milvus vs. ObjectBox vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Time Series DBMS

Vector DBMS

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	2.78
Rank	#103	Overall
	#4	Vector DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

github.com/graphite-project/graphite-web

milvus.io

github.com/objectbox
objectbox.io

www.snowflake.com

Technical documentation

graphite.readthedocs.io

milvus.io/docs/overview.md

docs.objectbox.io

docs.snowflake.net/manuals/index.html

Developer

Chris Davis

ObjectBox Limited

Snowflake Computing Inc.

Initial release

2006

2019

2017

2014

Current release

2.4.4, May 2024

4.0 (May 2024)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Bindings are released under Apache 2.0

Apache License 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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

Python

C++, Go

C and C++

Server operating systems

Linux
Unix

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

Numeric data only

Vector, Numeric and String

yes, plus "flex" map-like types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API
Sockets

RESTful HTTP API

Proprietary native API

CLI Client
JDBC
ODBC

Supported programming languages

JavaScript (Node.js)
Python

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Data sync between devices allowing occasional connected databases to work completely offline

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate 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

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

Role based access control and fine grained access rights

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

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...
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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

News

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

On-device Vector Database for Dart/Flutter
21 May 2024

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