DBMS > GridDB vs. OrientDB vs. Snowflake vs. Weaviate

System Properties Comparison GridDB vs. OrientDB vs. Snowflake vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

Multi-model DBMS (Document, Graph, Key/Value)

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

Time Series DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Vector DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

griddb.net

orientdb.org

www.snowflake.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.griddb.net

www.orientdb.com/docs/last/index.html

docs.snowflake.net/manuals/index.html

weaviate.io/developers/weaviate

Developer

Toshiba Corporation

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

Weaviate B.V.

Initial release

2013

2010

2014

2019

Current release

5.1, August 2022

3.2.29, March 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache version 2

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

C++

Java

Server operating systems

Linux

All OS with a Java JDK (>= JDK 6)

hosted

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language, no joins

yes

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java, Javascript

user defined functions

Triggers

yes

Hooks

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

Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID at container level

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

Access rights for users can be defined per database

Access rights for users and roles; record level security configurable

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

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
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All companies that have data.
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Market metrics

GitHub trending repository
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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

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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