DBMS > Amazon Redshift vs. Kinetica vs. Snowflake vs. WakandaDB vs. Weaviate

System Properties Comparison Amazon Redshift vs. Kinetica vs. Snowflake vs. WakandaDB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Fully vectorized database across both GPUs and CPUs

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

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

Primary database model

Relational DBMS

Object oriented DBMS

Vector DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Score	1.89
Rank	#138	Overall
	#4	Vector DBMS

Website

aws.amazon.com/redshift

www.kinetica.com

www.snowflake.com

wakanda.github.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.aws.amazon.com/redshift

docs.kinetica.com

docs.snowflake.net/manuals/index.html

wakanda.github.io/doc

weaviate.io/developers/weaviate

Developer

Amazon (based on PostgreSQL)

Kinetica

Snowflake Computing Inc.

Wakanda SAS

Weaviate B.V.

Initial release

2012

2014

2012

2019

Current release

7.1, August 2021

2.7.0 (April 29, 2019), April 2019

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

AGPLv3, extended commercial license available

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, C++

C++, JavaScript

Server operating systems

hosted

Linux

hosted

Linux
OS X
Windows

Data scheme

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

restricted

yes

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

JavaScript

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

none

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 or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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

yes

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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