DBMS > Google Cloud Datastore vs. Oracle NoSQL vs. Snowflake vs. Weaviate

System Properties Comparison Google Cloud Datastore vs. Oracle NoSQL vs. Snowflake vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

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

Primary database model

Document store

Document store
Key-value store
Relational DBMS

Relational DBMS

Vector DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

cloud.google.com/datastore

www.oracle.com/database/nosql/technologies/nosql

www.snowflake.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

cloud.google.com/datastore/docs

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.snowflake.net/manuals/index.html

weaviate.io/developers/weaviate

Developer

Google

Oracle

Snowflake Computing Inc.

Weaviate B.V.

Initial release

2008

2011

2014

2019

Current release

23.3, December 2023

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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.

Implementation language

Java

Server operating systems

hosted

Linux
Solaris SPARC/x86

hosted

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

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

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes, details here

optional

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

SQL-like query language (GQL)

SQL-like DML and DDL statements

yes

GraphQL is used as query language

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

CLI Client
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

using Google App Engine

user defined functions

Triggers

Callbacks using the Google Apps Engine

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

Multi-source replication using Paxos

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

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

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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