DBMS > CockroachDB vs. Google Cloud Firestore vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

System Properties Comparison CockroachDB vs. Google Cloud Firestore vs. IBM Db2 warehouse vs. Snowflake vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Relational DBMS

Document store

Relational DBMS

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

Score	6.10
Rank	#58	Overall
	#33	Relational DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	1.34
Rank	#166	Overall
	#76	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

www.cockroachlabs.com

firebase.google.com/products/firestore

www.ibm.com/products/db2/warehouse

www.snowflake.com

sqream.com

Technical documentation

www.cockroachlabs.com/docs

firebase.google.com/docs/firestore

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Cockroach Labs

Google

IBM

Snowflake Computing Inc.

SQream Technologies

Initial release

2015

2017

2014

2017

Current release

23.1.1, May 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

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

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
macOS
Windows

hosted

Linux

Data scheme

dynamic schema

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

JDBC

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

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

Supported programming languages

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

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

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

PL/SQL, SQL PL

user defined functions

user defined functions in Python

Triggers

yes, with Cloud Functions

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

yes

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication

yes

none

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.

yes

User concepts

Access control

Role-based access control

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

fine grained access rights according to SQL-standard

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

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