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Datomic VS Google Cloud PostgreSQL

Compare Datomic VS Google Cloud PostgreSQL and see what are their differences

Datomic logo Datomic

The fully transactional, cloud-ready, distributed database

Google Cloud PostgreSQL logo Google Cloud PostgreSQL

Fully-managed database service
  • Datomic Landing page
    Landing page //
    2023-09-14
  • Google Cloud PostgreSQL Landing page
    Landing page //
    2023-09-29

Datomic features and specs

  • Immutability
    Datomic employs an append-only data model where data is never overwritten but instead appended, ensuring historical data is always available and providing strong consistency.
  • Time Travel Queries
    Datomic allows you to query the database as of any point in time, facilitating auditing and debugging by allowing easy access to historical data states.
  • Rich Data Model
    Supports complex data types like maps and sets directly within its schema, providing a flexible way to represent data.
  • ACID Transactions
    Datomic supports fully ACID-compliant transactions, ensuring reliable and predictable database operations.
  • Scalability
    Separates storage and compute, allowing for horizontal scaling of read operations, making it suitable for handling large datasets.
  • Query Flexibility
    Offers a powerful query language that supports recursive queries, making it suitable for complex data retrieval needs.

Possible disadvantages of Datomic

  • Complexity
    The architecture of Datomic can be complex to understand and implement, particularly for teams unfamiliar with its design principles.
  • Cost
    Can be expensive to operate, especially in a cloud environment, where costs increase with the amount of data stored and the compute resources required.
  • Limited Write Throughput
    Due to its append-only design, Datomic can have limited write throughput, which may not be suitable for applications with heavy write requirements.
  • Closed Source
    Datomic is a proprietary database system, which may not appeal to organizations that prefer open-source solutions.
  • Learning Curve
    Requires a learning curve as its conceptual model and query language are different from traditional databases, potentially requiring additional training.
  • Dependency on AWS
    Relying on AWS ecosystem for the storage backend can limit choices for deployment environments, impacting flexibility.

Google Cloud PostgreSQL features and specs

  • Scalability
    Google Cloud PostgreSQL offers easy scalability for growing databases, allowing you to adjust resources like CPU and RAM without significant downtime.
  • Managed Service
    As a fully managed service, it reduces the overhead of database maintenance tasks such as backups, patching, and updates, allowing developers to focus on application development.
  • High Availability
    It provides high availability configurations with automated failover to ensure that your database is reliable and your application remains uninterrupted.
  • Security
    Offers strong security measures, including encryption at rest and in transit, and integration with Google Cloud's Identity and Access Management (IAM).
  • Integration
    Seamlessly integrates with other Google Cloud services, making it easier to build comprehensive cloud solutions.

Possible disadvantages of Google Cloud PostgreSQL

  • Cost
    The cost can become high compared to other options, especially if your database requirements grow significantly, leading to increased resource allocation.
  • Limited Customization
    Being a managed service, there may be limited ability to customize certain configurations compared to self-hosted PostgreSQL solutions.
  • Vendor Lock-in
    Using Google Cloud services can lead to dependency on their ecosystem, making it challenging to migrate to another platform or cloud provider in the future.
  • Latency
    While Google Cloud provides robust infrastructure, network latency can still be an issue, especially if the service is being accessed from geographically distant regions.
  • Complexity
    Navigating and configuring the myriad of available options in Google Cloud can be complex and requires a certain level of expertise, which might be burdensome for newcomers.

Datomic videos

KotlinConf 2018 - Datomic: The Most Innovative DB You've Never Heard Of by August Lilleaas

More videos:

  • Review - "Real-World Datomic: An Experience Report" by Craig Andera (2013)
  • Review - Rich Hickey on Datomic Ions, September 12, 2018

Google Cloud PostgreSQL videos

No Google Cloud PostgreSQL videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Datomic and Google Cloud PostgreSQL)
Databases
70 70%
30% 30
Developer Tools
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
Network & Admin
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Google Cloud PostgreSQL seems to be more popular. It has been mentiond 7 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.

Datomic mentions (0)

We have not tracked any mentions of Datomic yet. Tracking of Datomic recommendations started around Mar 2021.

Google Cloud PostgreSQL mentions (7)

  • Kubernetes and Container Portability: Navigating Multi-Cloud Flexibility
    Google Cloud SQL for MySQL (for managed MySQL) or Google Cloud SQL for PostgreSQL (for managed PostgreSQL). - Source: dev.to / over 1 year ago
  • Top 8 Managed Postgres Providers
    This is Google's managed service for databases that makes it easier to set up, maintain, and manage PostgreSQL databases on Google Cloud. - Source: dev.to / about 2 years ago
  • Questions about 'databaseing' on the Cloud
    For a small database you don't need Snowflake. You need Postgres or MySQL. Power BI for visualizing data seems fine. For entering data you can use Airforms. Source: about 3 years ago
  • Distributed Managed PostgreSQL Database Alternatives in the Cloud
    PostgreSQL is an open-source relational database, used by many companies, and is very common among cloud applications, where companies prefer an open-source solution, supported by a strong community, as an alternative to commercial database engines. The simplest way to run the PostgreSQL engine in the cloud is to choose one of the managed database services, such as Amazon RDS for PostgreSQL or Google Cloud SQL... - Source: dev.to / over 3 years ago
  • Get data from Cloud SQL with Python
    For the database, I used Cloud SQL, which is a managed database service from Google Cloud Platform (GCP). This GCP product provides a cloud-based alternative to MySQL, PostgreSQL and SQL Server databases. The great advantage of Cloud SQL is that it is a managed service, that is, you do not have to worry about some tasks related to the infrastructure where the database will run, tasks such as backups, maintenance... - Source: dev.to / about 4 years ago
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What are some alternatives?

When comparing Datomic and Google Cloud PostgreSQL, you can also consider the following products

MySQL - The world's most popular open source database

Supabase - An open source Firebase alternative

MarkLogic Server - MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities.

Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.

Valentina Server - Valentina Server is 3 in 1: Valentina DB Server / SQLite Server / Report Server

pREST - A fully RESTful API from any existing PostgreSQL database written in Go