DBMS > Databricks vs. Dgraph vs. Google Cloud Firestore vs. Snowflake

System Properties Comparison Databricks vs. Dgraph vs. Google Cloud Firestore vs. Snowflake

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Distributed and scalable native Graph DBMS

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

Primary database model

Document store
Relational DBMS

Graph DBMS

Document store

Relational DBMS

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

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.databricks.com

dgraph.io

firebase.google.com/products/firestore

www.snowflake.com

Technical documentation

docs.databricks.com

dgraph.io/docs

firebase.google.com/docs/firestore

docs.snowflake.net/manuals/index.html

Developer

Databricks

Dgraph Labs, Inc.

Google

Snowflake Computing Inc.

Initial release

2013

2016

2017

2014

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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

Server operating systems

hosted

Linux
OS X
Windows

hosted

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

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

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

with Databricks SQL

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Python
R
Scala

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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.

User concepts

Access control

Planned for future releases

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.