DBMS > Apache Drill vs. Atos Standard Common Repository vs. Google Cloud Firestore vs. Google Cloud Spanner vs. Snowflake

System Properties Comparison Apache Drill vs. Atos Standard Common Repository vs. Google Cloud Firestore vs. Google Cloud Spanner vs. Snowflake

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Document store

Relational DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

drill.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

firebase.google.com/products/firestore

cloud.google.com/spanner

www.snowflake.com

Technical documentation

drill.apache.org/docs

firebase.google.com/docs/firestore

cloud.google.com/spanner/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Atos Convergence Creators

Google

Snowflake Computing Inc.

Initial release

2012

2016

2017

2014

Current release

1.20.3, January 2023

1703

License

Commercial or Open Source

Open Source

Apache Version 2

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

Java

Server operating systems

Linux
OS X
Windows

Linux

hosted

Data scheme

schema-free

Schema and schema-less with LDAP views

schema-free

yes

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

Typing

predefined data types such as float or date

yes

optional

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

SQL SELECT statement is SQL:2003 compliant

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

LDAP

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C++

All languages with LDAP bindings

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

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication with 3 replicas for regional instances.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

yes

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

LDAP bind authentication

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

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

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

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