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Google Cloud Bigtable VS Amazon Aurora

Compare Google Cloud Bigtable VS Amazon Aurora and see what are their differences

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Google Cloud Bigtable logo Google Cloud Bigtable

A high performance NoSQL database service for large analytical and operational workloads.

Amazon Aurora logo Amazon Aurora

MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.
  • Google Cloud Bigtable Landing page
    Landing page //
    2023-09-12
  • Amazon Aurora Landing page
    Landing page //
    2023-03-17

Google Cloud Bigtable features and specs

  • Scalability
    Google Cloud Bigtable is designed to scale horizontally to handle massive amounts of data across millions of rows and thousands of columns. This makes it ideal for applications needing to handle large datasets with high throughput.
  • Low Latency
    Bigtable is optimized for low-latency access to big data. It is capable of delivering real-time responses, which is beneficial for applications that require fast read and write operations.
  • Seamless Integration
    Bigtable integrates easily with other GCP services like Google Cloud Storage, BigQuery, and Dataflow, simplifying the development of complex applications that require various cloud services.
  • Managed Service
    As a managed service, Bigtable handles routine operations such as scaling, replication, and failure recovery, allowing users to focus on application development rather than infrastructure management.
  • Strong Consistency
    Bigtable provides strong consistency for read and write operations, ensuring that data is reliable and consistent across operations and query results.

Possible disadvantages of Google Cloud Bigtable

  • Complexity of Use
    Bigtable can be complex to set up and use effectively, especially for those who are unfamiliar with NoSQL databases or distributed systems.
  • Cost
    While scalable, the pricing can become expensive as your requirements grow, especially if you need high throughput and large storage capacities.
  • Limited Querying Capabilities
    Unlike relational databases, Bigtable has limited querying capabilities. It does not support SQL-like queries, making it less suitable for applications that require complex querying options.
  • Region-Specific Availability
    Bigtable is available only in certain regions, which might limit its use for global applications requiring multi-region deployments for latency optimization.
  • Learning Curve
    There's a significant learning curve for new users to understand Bigtable's architecture and its best practices, which can delay the development process.

Amazon Aurora features and specs

  • High Performance
    Amazon Aurora is designed to provide up to five times the throughput of standard MySQL and three times the throughput of standard PostgreSQL databases.
  • Scalability
    Aurora scales storage automatically, growing from 10GB up to 128TB with no downtime. This automatic scaling makes it ideal for applications with fluctuating workloads.
  • High Availability and Durability
    Aurora automatically replicates six copies of data across three availability zones and continuously backs up data to Amazon S3, ensuring durability.
  • Security
    Aurora offers multiple layers of security including network isolation using Amazon VPC, encryption at rest using keys that you create and control through AWS Key Management Service (KMS), and encryption of data in transit using SSL.
  • Fully Managed
    Aurora is fully managed by AWS, which automates time-consuming administrative tasks such as hardware provisioning, database setup, patching, and backups.
  • Compatibility
    Aurora is compatible with MySQL and PostgreSQL, making it easier to migrate existing applications to Aurora with minimal changes.

Possible disadvantages of Amazon Aurora

  • Cost
    Aurora can be more expensive than traditional RDS instances, particularly for workloads that do not fully utilize its high performance and scalability features.
  • Complexity
    The numerous features and configurations can make Aurora complex to manage and tune, especially for those who are not familiar with AWS services.
  • Vendor Lock-in
    Adopting Aurora ties you into the AWS ecosystem, which can make it difficult to migrate to other cloud providers or on-premises systems.
  • Cold Start Latency
    Aurora Serverless can experience latency during cold starts, which can be problematic for applications requiring instant scalability.
  • Limited to AWS Environment
    Aurora is only available within the AWS environment, which can be limiting if your infrastructure spans multiple cloud providers.

Analysis of Amazon Aurora

Overall verdict

  • Amazon Aurora is generally regarded as an excellent database service for businesses that require robust performance and high availability. It strikes a balance between cost-effectiveness and advanced database features, making it suitable for a wide range of applications.

Why this product is good

  • Amazon Aurora is considered a good choice for many applications due to its high performance, scalability, and compatibility with popular database systems like MySQL and PostgreSQL. It offers features like automated backups, quick failover, and replication capabilities. Aurora is designed to be fault-tolerant and highly available, providing a fully managed solution that relieves users from the operational burden associated with on-premise database management.

Recommended for

    Amazon Aurora is recommended for organizations that need reliable, scalable, and high-performance databases. It is well-suited for web and mobile applications, e-commerce platforms, real-time analytics, and other use cases requiring high availability and fault tolerance. It's ideal for businesses looking to modernize their database infrastructure and take advantage of cloud-native capabilities.

Google Cloud Bigtable videos

+ Add

Scalability Meetup @ Whitepages - Google Cloud BigTable

Amazon Aurora videos

+ Add

Introduction to Amazon Aurora - Relational Database Built for the Cloud - AWS

More videos:

  • Review - Amazon Aurora Global Database Deep Dive
  • Review - What's New in Amazon Aurora - AWS Online Tech Talks

Category Popularity

0-100% (relative to Google Cloud Bigtable and Amazon Aurora)

Google Cloud Bigtable

Amazon Aurora

Databases
15 15%
Databases
85% 85
NoSQL Databases
23 23%
NoSQL Databases
77% 77
Relational Databases
11 11%
Relational Databases
89% 89
Developer Tools
100 100%
Developer Tools
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google Cloud Bigtable and Amazon Aurora

Google Cloud Bigtable Reviews

7 Best NoSQL APIs
When businesses need to scale, they want to do so with limited downtime. The Google Cloud Bigtable provides horizontal Scaling in a matter of seconds without any downtime. To scale, cluster nodes are quickly added to increase your overall Bigtable cluster. Google even provides the option of scaling out only for a matter of hours, to handle a large load of requests. Once the...
Source: www.programmableweb.com

Amazon Aurora Reviews

We have no reviews of Amazon Aurora yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Amazon Aurora should be more popular than Google Cloud Bigtable. It has been mentiond 23 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google Cloud Bigtable mentions (6)

  • Vaultree and AlloyDB: the world's first Fully Homomorphic and Searchable Cloud Encryption Solution
    In my opinion, Google has built some fantastic database services like Bigtable and Spanner, which literally changed the industry for good, and I am eager to see how they will build upon this new service. With AlloyDB's disaggregated architecture, the dystopian world where I only pay for SQL databases per query and the stored data on GCP seems closer than ever. - Source: dev.to / over 2 years ago
  • Google Cloud Reference
    Cloud Bigtable: Petabyte-scale, low-latency, non-relational 🔗Link 🔗Link. - Source: dev.to / almost 3 years ago
  • A Graph-Based Firebase
    > These triples say that the Layer with id 1 has a fontSize 20 and backgroundColor blue. Since they are different rows, there’s no conflict. This sounds a lot like Bigtable (https://cloud.google.com/bigtable), which also does last-write-wins conflict resolution layer. So this is adding a GraphQL + frontend layer to it? - Source: Hacker News / almost 3 years ago
  • The 4 Types of NoSQL Databases You Need to Know
    Google's BigTable paper inspired this database design, and it is capable of handling large data loads on distributed machines. In addition, column-oriented databases provide efficient compression and high performance with aggregated queries such as sum, average, and minimum. - Source: dev.to / almost 3 years ago
  • Can someone help me understand why data batch processing and data streaming processing pose such different challenges in data management?
    Because of these and other differences, the tools used are also different. With batch processing, data might be read from large files, processed, and stored in an OLTP (Online Transaction Processing) database (like MySQL) or OLAP (Online Analytical Processing) system (like Google BigQuery). But these would not be good solutions for streaming applications, because they are not optimized for high throughput on a lot... Source: over 3 years ago
View more

Amazon Aurora mentions (23)

  • Building a RAG System for Video Content Search and Analysis
    Using Amazon Bedrock to invoke Amazon Titan Foundation Models for generating multimodal embeddings, Amazon Transcribe for converting speech to text, and Amazon Aurora postgreSQL for vector storage and similarity search, you can build an application that understands both visual and audio content, enabling natural language queries to find specific moments in videos. - Source: dev.to / about 2 months ago
  • Everyone Uses Postgres… But Why?
    Cloud deployment: PostgreSQL can be deployed in the cloud with AWS RDS, Amazon Aurora, Azure Database for PostgreSQL, or Cloud SQL for PostgreSQL. - Source: dev.to / 6 months ago
  • Announcing the public beta for dedicated clusters
    Today, our Postgres databases are Amazon Aurora instances. You can trust that your database will have the scalability, reliability and security that AWS is known for. With dedicated clusters you can configure both the Postgres engine version, cluster class and number of replicas for failover and query distribution. - Source: dev.to / 10 months ago
  • Vector database is not a separate database category
    As far as the big players are concerned, Google offers AlloyDB (https://cloud.google.com/alloydb) while Amazon offers Aurora (https://aws.amazon.com/rds/aurora/). - Source: Hacker News / over 1 year ago
  • Building realtime experiences with Amazon Aurora
    Aurora is a managed database service from Amazon compatible with MySQL and PostgreSQL. It allows for the use of existing MySQL code, tools, and applications and can offer increased performance for certain workloads compared to MySQL and PostgreSQL. - Source: dev.to / almost 2 years ago
View more

What are some alternatives?

When comparing Google Cloud Bigtable and Amazon Aurora, you can also consider the following products

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Azure Cosmos DB - NoSQL JSON database for rapid, iterative app development.

MySQL - The world's most popular open source database

Google Cloud Spanner - Google Cloud Spanner is a horizontally scalable, globally consistent, relational database service.

Oracle DBaaS - See how Oracle Database 12c enables businesses to plug into the cloud and power the real-time enterprise.

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