DBMS > Milvus vs. Snowflake vs. SurrealDB vs. TempoIQ vs. Weaviate

System Properties Comparison Milvus vs. Snowflake vs. SurrealDB vs. TempoIQ vs. Weaviate

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Vector DBMS

Relational DBMS

Document store
Graph DBMS

Time Series DBMS

Vector DBMS

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

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

milvus.io

www.snowflake.com

surrealdb.com

tempoiq.com (offline)

github.com/weaviate/weaviate
weaviate.io

Technical documentation

milvus.io/docs/overview.md

docs.snowflake.net/manuals/index.html

surrealdb.com/docs

weaviate.io/developers/weaviate

Developer

Snowflake Computing Inc.

SurrealDB Ltd

TempoIQ

Weaviate B.V.

Initial release

2019

2014

2022

2012

2019

Current release

2.3.4, January 2024

v1.5.0, May 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

commercial

Open Source

commercial license available with Weaviate Enterprise

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

C++, Go

Rust

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

hosted

Linux
macOS
Windows

Data scheme

yes

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

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

Vector, Numeric and String

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

yes

SQL-like query language

GraphQL is used as query language

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

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

JavaScript (Node.js)
Python

Deno
Go
JavaScript (Node.js)
Rust

C#
Java
JavaScript

Node.js
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Immediate Consistency

Eventual 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

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

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

yes, based on authentication and database rules

simple authentication-based access control

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Highly available, versatile, and robust with millisecond latency. Supports batch...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

RAG: retrieval augmented generation Video media : video understanding, video deduplication....
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
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All companies that have data.
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Market metrics

As of January 2024, 25k+ GitHub stars 10M+ downloads and installations 3k+ enterprise...
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As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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