DBMS > Galaxybase vs. Snowflake vs. Tigris vs. Weaviate

System Properties Comparison Galaxybase vs. Snowflake vs. Tigris vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

Primary database model

Graph DBMS

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Vector DBMS

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

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.02
Rank	#369	Overall
	#51	Document stores
	#55	Key-value stores
	#24	Search engines
	#38	Time Series DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

galaxybase.com

www.snowflake.com

www.tigrisdata.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.snowflake.net/manuals/index.html

www.tigrisdata.com/docs

weaviate.io/developers/weaviate

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Snowflake Computing Inc.

Tigris Data, Inc.

Weaviate B.V.

Initial release

2017

2014

2022

2019

Current release

Nov 20, November 2021

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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.

Implementation language

C and Java

Server operating systems

Linux

hosted

Linux
macOS
Windows

Data scheme

Strong typed schema

yes

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

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

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

GraphQL is used as query language

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

CLI Client
JDBC
ODBC

CLI Client
gRPC
RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined procedures and functions

user defined functions

Triggers

similar concept for controling cloud resources

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

yes, using FoundationDB

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

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

Access rights for users and roles

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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