DBMS > Firebase Realtime Database vs. Google Cloud Bigtable vs. Hawkular Metrics vs. TypeDB

System Properties Comparison Firebase Realtime Database vs. Google Cloud Bigtable vs. Hawkular Metrics vs. TypeDB

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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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store

Key-value store
Wide column store

Time Series DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

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

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	0.81
Rank	#217	Overall
	#19	Graph DBMS
	#99	Relational DBMS

Website

firebase.google.com/products/realtime-database

cloud.google.com/bigtable

www.hawkular.org

typedb.com

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigtable/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

typedb.com/docs

Developer

Google

acquired by Google 2014

Google

Community supported by Red Hat

Vaticle

Initial release

2012

2015

2014

2016

Current release

2.26.3, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL Version 3, commercial licenses 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

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

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

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

Java
JavaScript
Objective-C

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

Go
Java
Python
Ruby

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor

based on Cassandra

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

substituted by the relationship feature

Transaction concepts

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

yes

Atomic single-row operations

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

yes, based on authentication and database rules

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

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more

Competitive advantages

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
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Typical application scenarios

Life sciences : TypeDB makes working with biological data much easier and accelerates...
» more

Licensing and pricing models

Apache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources

DB-Engines blog posts

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