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Datomic VS Azure Cosmos DB

Compare Datomic VS Azure Cosmos DB and see what are their differences

Datomic logo Datomic

The fully transactional, cloud-ready, distributed database

Azure Cosmos DB logo Azure Cosmos DB

NoSQL JSON database for rapid, iterative app development.
  • Datomic Landing page
    Landing page //
    2023-09-14
  • Azure Cosmos DB Landing page
    Landing page //
    2023-03-16

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.

Azure Cosmos DB features and specs

  • Global Distribution
    Azure Cosmos DB allows for the distribution of data across multiple global regions, enhancing availability and delivering low-latency access to data for users around the world.
  • Multi-Model Support
    It supports multiple data models including document, graph, key-value, and column-family APIs, making it versatile for a variety of applications and use cases.
  • Automatic Scaling
    The database automatically scales up and down to meet the demands of application traffic, helping to manage workloads efficiently without manual intervention.
  • High Throughput and Low Latency
    Cosmos DB offers high performance with single-digit millisecond read and write latencies, ensuring fast access to data for applications.
  • Comprehensive SLAs
    Azure Cosmos DB provides industry-leading SLAs covering availability, throughput, consistency, and latency, offering strong guarantees for customers.
  • Integrated Security
    It includes robust security features such as SSL/TLS encryption, role-based access control, and integration with Azure Active Directory for secure data management.

Possible disadvantages of Azure Cosmos DB

  • Cost
    Azure Cosmos DB can be expensive, especially for high-throughput workloads and global distribution scenarios. Its pricing model based on provisioned throughput (RU/s) can add up quickly.
  • Complexity
    Managing and optimizing Cosmos DB can be complex, requiring a deep understanding of its configuration settings, partitioning strategies, and indexing to achieve optimal performance.
  • Vendor Lock-In
    As a proprietary service, using Cosmos DB tightly couples your application to Azure. This can make it difficult to migrate to other database solutions or cloud providers in the future.
  • Consistency Models
    Azure Cosmos DB supports multiple consistency levels which can introduce complexity in designing applications. Developers need to understand and choose the appropriate consistency level for their specific use case.
  • Limited Native Analytics
    Cosmos DB does not have built-in advanced analytics capabilities. Integrating with other services like Azure Synapse or Databricks may be necessary for sophisticated data analytics and reporting.

Analysis of Azure Cosmos DB

Overall verdict

  • Azure Cosmos DB is generally regarded as a robust and versatile database solution, particularly suited for applications that require flexibility, scale, and low-latency global access. It is a good option for developers looking to leverage Azure's cloud ecosystem.

Why this product is good

  • Azure Cosmos DB is a globally distributed, multi-model database service that offers turnkey global distribution, horizontal scaling, and a comprehensive SLA covering throughput, latency, availability, and consistency. It is designed to provide high availability and seamless integration with Azure services, making it a good fit for applications requiring low-latency and the ability to scale across multiple regions.

Recommended for

  • Organizations needing globally distributed applications
  • Developers working within the Azure ecosystem
  • Applications requiring multi-model database capabilities
  • Scenarios demanding high availability and low latency
  • Projects where seamless scalability is a priority

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

Azure Cosmos DB videos

Azure Cosmos DB: Comprehensive Overview

More videos:

  • Review - Azure Friday | Azure Cosmos DB with Scott Hanselman
  • Tutorial - Azure Cosmos DB Tutorial | Globally distributed NoSQL database

Category Popularity

0-100% (relative to Datomic and Azure Cosmos DB)
Databases
30 30%
70% 70
Relational Databases
66 66%
34% 34
NoSQL Databases
17 17%
83% 83
Network & Admin
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Azure Cosmos DB seems to be more popular. It has been mentiond 9 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.

Azure Cosmos DB mentions (9)

  • Blazor server app, deployment options
    If you are writing the code maybe consider learning Cosmos DB it’s pretty easy to work with and there is a free tier. Also in my experience it’s much faster than a SQL database. Source: about 2 years ago
  • Infrastructure as code (IaC) for Java-based apps on Azure
    Sometimes you don’t need an entire Java-based microservice. You can build serverless APIs with the help of Azure Functions. For example, Azure functions have a bunch of built-in connectors like Azure Event Hubs to process event-driven Java code and send the data to Azure Cosmos DB in real-time. FedEx and UBS projects are great examples of real-time, event-driven Java. I also recommend you to go through 👉 Code,... - Source: dev.to / over 2 years ago
  • Deploying a Mostly Serverless Website on GCP
    When debating the database solution for our application we were really seeking for a scalable serverless database that wouldn’t bill us for idle time. Options like AWS Athena, AWS Aurora Serverless, and Azure Cosmos DB immediately came to mind. We believed that GCP would have a comparable service, yet we could not find one. Even after consulting the GCP cloud service comparison documentation we were still unable... - Source: dev.to / almost 3 years ago
  • Which DB to use for API published on Azure?
    If you are looking for one to start with; you can try Cosmos: https://azure.microsoft.com/en-us/services/cosmos-db/. Source: about 3 years ago
  • Basic Setup for Azure Cosmos DB and Example Node App
    I have had an opportunity to work on a project that uses Azure Cosmos DB with the MongDB API as the backend database. I wanted to spend a little more time on my own understanding how to perform basic setup and a simple set of CRUD operations from a Node application, as well as construct an easy-to-follow procedure for other developers. - Source: dev.to / about 3 years ago
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What are some alternatives?

When comparing Datomic and Azure Cosmos DB, you can also consider the following products

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

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Datahike - A durable datalog database adaptable for distribution.

ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Matisse - Matisse is a post-relational SQL database.

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