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  1. Stackups
  2. Application & Data
  3. NoSQL Databases
  4. NOSQL Database As A Service
  5. Firebase Realtime Database vs Google Cloud Bigtable

Firebase Realtime Database vs Google Cloud Bigtable

OverviewComparisonAlternatives

Overview

Google Cloud Bigtable
Google Cloud Bigtable
Stacks173
Followers363
Votes25
Firebase Realtime Database
Firebase Realtime Database
Stacks107
Followers229
Votes7

Firebase Realtime Database vs Google Cloud Bigtable: What are the differences?

Differences between Firebase Realtime Database and Google Cloud Bigtable

Firebase Realtime Database and Google Cloud Bigtable are both cloud database solutions offered by Google. While they have some similarities, there are key differences that set them apart.

  1. Data Model: Firebase Realtime Database is a NoSQL database that uses a JSON data model. It provides a flexible structure for storing and retrieving data, making it suitable for real-time applications. On the other hand, Google Cloud Bigtable is a wide-column NoSQL database that stores data in tables comprised of rows and columns. It is designed for handling massive amounts of data with low latency, making it a good fit for big data applications.

  2. Scalability: Firebase Realtime Database provides automatic scaling as the database usage grows. It can handle high concurrency and supports millions of concurrent connections, making it ideal for real-time synchronization of data across multiple devices. In comparison, Google Cloud Bigtable is built for massive scalability and can easily handle petabytes of data. It is designed to handle high read and write throughput, which makes it suitable for applications that require high performance and scalability.

  3. Querying: Firebase Realtime Database offers a flexible querying system with a simple API. It supports querying based on specific values or ranges and allows for sorting and filtering of data. However, it does not support complex querying operations like JOINs or aggregations. On the other hand, Google Cloud Bigtable does not offer built-in querying capabilities. It is a key-value store and requires the use of additional tools or frameworks for querying and analysis.

  4. Data Consistency: Firebase Realtime Database provides real-time synchronization and offers strong data consistency within a single user session. However, in a multi-user scenario, there can be eventual consistency issues. On the other hand, Google Cloud Bigtable offers strong consistency guarantees for single-row transactions, but its design allows for eventual consistency for multi-row transactions.

  5. Pricing: Firebase Realtime Database pricing is based on data transfer and storage volume. It offers a free tier that provides limited usage and additional pricing plans based on usage. In comparison, Google Cloud Bigtable pricing is based on the amount of data stored and the operations performed. It offers different pricing tiers based on performance and capacity requirements.

  6. Integration with other Google Services: Firebase Realtime Database is part of the Firebase suite of services, providing easy integration with other Firebase services like authentication, hosting, and notifications. It also provides integration with Google Analytics for tracking and analyzing data. On the other hand, Google Cloud Bigtable is part of the Google Cloud Platform ecosystem, allowing for seamless integration with other Google Cloud services like BigQuery, Dataflow, and Dataproc.

In summary, Firebase Realtime Database is a NoSQL database with a JSON data model, suitable for real-time synchronization and flexible querying. Google Cloud Bigtable is a wide-column NoSQL database designed for massive scalability, high performance, and integration with other Google Cloud services.

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Detailed Comparison

Google Cloud Bigtable
Google Cloud Bigtable
Firebase Realtime Database
Firebase Realtime Database

Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.

It is a cloud-hosted NoSQL database that lets you store and sync data between your users in realtime. Data is synced across all clients in realtime, and remains available when your app goes offline.

Unmatched Performance: Single-digit millisecond latency and over 2X the performance per dollar of unmanaged NoSQL alternatives.;Open Source Interface: Because Cloud Bigtable is accessed through the HBase API, it is natively integrated with much of the existing big data and Hadoop ecosystem and supports Google’s big data products. Additionally, data can be imported from or exported to existing HBase clusters through simple bulk ingestion tools using industry-standard formats.;Low Cost: By providing a fully managed service and exceptional efficiency, Cloud Bigtable’s total cost of ownership is less than half the cost of its direct competition.;Security: Cloud Bigtable is built with a replicated storage strategy, and all data is encrypted both in-flight and at rest.;Simplicity: Creating or reconfiguring a Cloud Bigtable cluster is done through a simple user interface and can be completed in less than 10 seconds. As data is put into Cloud Bigtable the backing storage scales automatically, so there’s no need to do complicated estimates of capacity requirements.;Maturity: Over the past 10+ years, Bigtable has driven Google’s most critical applications. In addition, the HBase API is a industry-standard interface for combined operational and analytical workloads.
Real time syncing for JSON data;Collaborate across devices with ease;Build serverless apps;Optimized for offline use;Strong user-based security
Statistics
Stacks
173
Stacks
107
Followers
363
Followers
229
Votes
25
Votes
7
Pros & Cons
Pros
  • 11
    High performance
  • 9
    Fully managed
  • 5
    High scalability
Pros
  • 7
    Very fast
  • 0
    Casandra
Cons
  • 2
    Poor query
Integrations
Heroic
Heroic
Hadoop
Hadoop
Apache Spark
Apache Spark
C++
C++
iOS
iOS
Unity
Unity
Firebase Authentication
Firebase Authentication
Android OS
Android OS
Cloud Functions for Firebase
Cloud Functions for Firebase

What are some alternatives to Google Cloud Bigtable, Firebase Realtime Database?

Amazon DynamoDB

Amazon DynamoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

Azure Cosmos DB

Azure Cosmos DB

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

Cloud Firestore

Cloud Firestore

Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.

Cloudant

Cloudant

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

Google Cloud Datastore

Google Cloud Datastore

Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.

CloudBoost

CloudBoost

CloudBoost.io is a database service for the “next web” - that not only does data-storage, but also search, real-time and a whole lot more which enables developers to build much richer apps with 50% less time saving them a ton of cost and helping them go to market much faster.

restdb.io

restdb.io

RestDB is a NoSql document oriented database cloud service. Data is accessed as JSON objects via HTTPS. This gives great flexibility, easy system integration and future compatibility.

Amazon DocumentDB

Amazon DocumentDB

Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

Amazon SimpleDB

Amazon SimpleDB

Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. Amazon SimpleDB provides a simple web services interface to create and store multiple data sets, query your data easily, and return the results. Your data is automatically indexed, making it easy to quickly find the information that you need. There is no need to pre-define a schema or change a schema if new data is added later. And scale-out is as simple as creating new domains, rather than building out new servers.

Datomic Cloud

Datomic Cloud

A transactional database with a flexible data model, elastic scaling, and rich queries. Datomic is designed from the ground up to run on AWS. Datomic leverages AWS technology, including DynamoDB, S3, EFS, and CloudFormation to provide a fully integrated solution.

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