DBMS > CrateDB vs. Google Cloud Firestore vs. IBM Db2

System Properties Comparison CrateDB vs. Google Cloud Firestore vs. IBM Db2

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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.

Common in IBM host environments, 2 different versions for host and Windows/Linux

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Secondary database models

Relational DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

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

Score	0.66
Rank	#223	Overall
	#37	Document stores
	#5	Spatial DBMS
	#17	Search engines
	#19	Time Series DBMS
	#15	Vector DBMS

Score	7.11
Rank	#47	Overall
	#8	Document stores

Score	126.57
Rank	#9	Overall
	#6	Relational DBMS

Website

cratedb.com

firebase.google.com/products/firestore

www.ibm.com/products/db2

Technical documentation

cratedb.com/docs

firebase.google.com/docs/firestore

www.ibm.com/docs/en/db2

Developer

Crate

Google

IBM

Initial release

2013

2017

1983

host version

Current release

5.8.1, August 2024

12.1, October 2016

License

Commercial or Open Source

Open Source

commercial

free version is available

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

C and C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Data scheme

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

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication

yes

with separate tools (MQ, InfoSphere)

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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

rights management via user accounts

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

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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