DBMS > Firebase Realtime Database vs. Google BigQuery vs. Immudb vs. jBASE vs. Postgres-XL

System Properties Comparison Firebase Realtime Database vs. Google BigQuery vs. Immudb vs. jBASE vs. Postgres-XL

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.

Large scale data warehouse service with append-only tables

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

A robust multi-value DBMS comprising development tools and middleware

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

github.com/codenotary/immudb
immudb.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.postgres-xl.org

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

docs.immudb.io

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.postgres-xl.org/documentation

Developer

Google

acquired by Google 2014

Google

Codenotary

Rocket Software (formerly Zumasys)

Initial release

2012

2010

2020

1991

2014

since 2012, originally named StormDB

Current release

1.2.3, April 2022

5.7

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Mozilla public license

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

BSD
Linux
macOS
Solaris
Windows
z/OS

AIX
Linux
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like syntax

Embedded SQL for jBASE in BASIC

yes

distributed, parallel query execution

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
Python

.Net
Basic
Jabbascript
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

in JavaScript

yes

user defined functions

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

ACID

MVCC

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

yes, based on authentication and database rules

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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