Software Alternatives, Accelerators & Startups

JSON Query VS Datomic

Compare JSON Query VS Datomic and see what are their differences

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JSON Query logo JSON Query

A tool to query JSON data structures

Datomic logo Datomic

The fully transactional, cloud-ready, distributed database
  • JSON Query Landing page
    Landing page //
    2020-02-04
  • Datomic Landing page
    Landing page //
    2023-09-14

JSON Query features and specs

  • Flexibility
    Allows you to query JSON data in a flexible manner, making it easier to extract specific information without altering the data structure.
  • Ease of Use
    The tool provides a user-friendly interface which makes it accessible even for users who are not very familiar with JSON data querying.
  • Efficiency
    Enables efficient data extraction, which can save time when dealing with large JSON datasets.
  • Compatibility
    Compatible with various JSON-based services and applications, facilitating integration into existing workflows.

Possible disadvantages of JSON Query

  • Learning Curve
    Users new to JSON Query language may need time to learn and become proficient in using the tool effectively.
  • Limited Advanced Features
    Might lack some advanced querying features found in more sophisticated query languages, potentially limiting its use for complex queries.
  • Dependency on Internet
    Since it's a web-based tool, it requires an internet connection, which may not be ideal in offline environments.
  • Performance Limitations
    Performance might degrade when processing extremely large JSON files or datasets, limiting its use for extensive data processing tasks.

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.

JSON Query videos

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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

Category Popularity

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Developer Tools
100 100%
0% 0
Databases
0 0%
100% 100
Productivity
100 100%
0% 0
Relational Databases
0 0%
100% 100

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What are some alternatives?

When comparing JSON Query and Datomic, you can also consider the following products

Redash - Data visualization and collaboration tool.

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

Search Console Data Exporter - Export 25,000 rows of query data from Google Search Console

Matisse - Matisse is a post-relational SQL database.

Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.

Datahike - A durable datalog database adaptable for distribution.