DBMS > Snowflake vs. Stardog vs. Weaviate

System Properties Comparison Snowflake vs. Stardog vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A cloud-native, realtime vector search engine integrating scalable machine learning models

Primary database model

Relational DBMS

Graph DBMS
RDF store

Search engine

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

Score	15.53
Rank	#37	Overall
	#22	Relational DBMS

Score	1.47
Rank	#144	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.00
Rank	#334	Overall
	#18	Search engines

Website

www.snowflake.com

www.stardog.com

github.com/semi-technologies/weaviate
www.semi.technology/solutions/weaviate

Technical documentation

docs.snowflake.net/manuals/index.html

www.stardog.com/docs

www.semi.technology/documentation/weaviate/current

Developer

Snowflake Computing Inc.

Stardog-Union

SeMI Technologies B.V.

Initial release

2014

2010

2017

Current release

7.3.0, May 2020

1.0.3, January 2021

License

Commercial or Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Java

Server operating systems

hosted

Linux
macOS
Windows

Data scheme

yes

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

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

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

SQL

Support of SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

GraphQL is used as query language

APIs and other access methods

CLI Client
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

similar concept for controling cloud resources

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in HA-Cluster

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Eventual Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

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

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

Access rights for users and roles

OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Stardog is an Enterprise Knowledge Graph platform, uniquely combining graph storage...
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Competitive advantages

Stardog provides a full featureset to aid in data integration for your complex data....
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Typical application scenarios

Stardog is frequently used for: Anti-money laundering & fraud monitoring Customer...
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Key customers

Bosch, Dow Jones, Elsevier, Ericsson, Morgan Stanley, NASA, NIH, Nokia, Salesforce,...
» more

Market metrics

Stardog's technology is based on ground-breaking research by our founders cited 10,000+...
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Licensing and pricing models

A fully-featured 60-day Trial license is available for those testing Stardog; contact...
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News

Weaviate in IEEE

Weaviate on DB-engines.com

Introduction & Demo video

FLOSS Weekly Podcast

FOSDEM 2020 video

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