DBMS > Firebase Realtime Database vs. Microsoft SQL Server vs. Tigris vs. Weaviate

System Properties Comparison Firebase Realtime Database vs. Microsoft SQL Server vs. Tigris vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Microsofts flagship relational DBMS

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

Document store

Relational DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#6	Vector DBMS

Website

firebase.google.com/products/realtime-database

www.microsoft.com/en-us/sql-server

www.tigrisdata.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

firebase.google.com/docs/database

learn.microsoft.com/en-US/sql/sql-server

www.tigrisdata.com/docs

weaviate.io/developers/weaviate

Developer

Google

acquired by Google 2014

Microsoft

Tigris Data, Inc.

Weaviate B.V.

Initial release

2012

1989

2022

2019

Current release

SQL Server 2022, November 2022

1.19, May 2023

License

Commercial or Open Source

commercial

restricted free version is available

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

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Implementation language

C++

Server operating systems

hosted

Linux
Windows

Linux
macOS
Windows

Data scheme

schema-free

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

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

CLI Client
gRPC
RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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.
» more

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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