Software Alternatives & Startups

Datahike VS dbForge SQL Complete

Compare Datahike VS dbForge SQL Complete and see what are their differences

Datahike

A durable datalog database adaptable for distribution.

Rating
0 reviews
dbForge SQL Complete

Try Intellisense functionality and Improved SQL Formatter in SQL Server Management Studio and Visual Studio using SQL Complete!

Rating
0 reviews
Pricing
Freemium Free trial $129.95 / Annually

Which is more popular?

Based on our record, Datahike seems to be more popular. It has been mentioned 6 times since March 2021.

social mentions
6 vs 0
Databases popularity
57% vs 43%
alternatives listed
39 vs 62

Base details

Website, pricing, platforms and company facts side by side.

Datahike
dbForge SQL Complete
Website github.com devart.com
Pricing —
Freemium Free trial $129.95 / Annually Official pricing
Listed in

About Datahike and dbForge SQL Complete

In their own words, as submitted to SaaSHub.

Datahike
dbForge SQL Complete

No description of Datahike yet.

dbForge SQL Complete is an add-in for SQL Server Management Studio and Visual Studio that speeds up SQL code writing, offers context-based smart suggestions, performs automatic formatting, refactoring and a lot of other things that save your time and effort in the database development process.

Read more about dbForge SQL Complete

Features and specs

What each product offers, as listed by its team.

Datahike 7 features
dbForge SQL Complete 6 features
  • Persistence
    Datahike is a persistent database, which means that it retains data across sessions and can be relied upon for storage that survives application restarts.
  • Datalog queries
    Datahike supports Datalog queries, a powerful and expressive query language that is similar to Prolog, allowing for complex querying of data relationships.
  • Schema flexibility
    Datahike provides schema flexibility that allows developers to define and evolve their data models without needing to perform migrations. This can significantly speed up development.
  • Immutable data structures
    By utilizing immutable data structures, Datahike allows safe concurrent reads and writes, reducing the risk of data corruption and improving application stability.
  • Transactional support
    Datahike offers ACID-compliant transactions, ensuring data integrity and consistent state even in the face of concurrent operations.
  • Integration with Datomic API
    Datahike is designed to be compatible with the Datomic API, making it easier for developers familiar with Datomic to transition and leverage their knowledge.
  • Off-the-shelf scalability
    The architecture of Datahike is conducive to scaling horizontally, providing flexibility to handle growing amounts of data and user load.

Possible disadvantages

  • Relatively new ecosystem
    Being a lesser-known and newer alternative compared to databases like Datomic, Datahike may have a smaller community and fewer resources like documentation and third-party integrations.
  • Performance limitations
    While Datahike is designed to be lightweight and flexible, it may not match the performance of more mature databases, especially in very high-load or high-volume scenarios.
  • Limited features
    Datahike may lack some advanced features present in other databases, such as sophisticated indexing or native support for certain types of analytics, which could be necessary for specific applications.
  • Java Virtual Machine (JVM) requirement
    As it runs on the JVM, Datahike requires a Java runtime environment, which might not be ideal or convenient for projects seeking to minimize dependencies or employ lightweight deployment strategies.
  • IntelliSense
    Provides advanced code completion features that help increase productivity by suggesting keywords, table names, and other SQL elements as you type.
  • Code Formatting
    Allows for customizable SQL code formatting to maintain consistent code style and readability across teams.
  • Code Snippets
    Offers a library of snippets for commonly used SQL statements, enabling users to quickly insert complex statements without typing them out.
  • SQL Refactoring
    Facilitates easy refactoring of SQL code, which helps in maintaining and improving existing codebases without altering its functionality.
  • Execution Plan
    Visualizes the execution plan of a query, aiding in performance optimization by identifying bottlenecks and inefficient operations.
  • Data Generation
    Includes capabilities for generating realistic test data, which is useful for development and testing purposes.

Videos

Walkthroughs and reviews on video.

Datahike 0 videos + Add
dbForge SQL Complete 1 video + Add

No Datahike videos yet. You could help us improve this page by suggesting one.

SQL Debugger in the new version of dbForge SQL Complete

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Datahike
dbForge SQL Complete
57% 57%
43% 43%
0% 0%
100% 100%
100% 100%
0% 0%
100% 100%
0% 0%

User comments

Share your experience with using Datahike and dbForge SQL Complete. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Datahike 6 mentions
dbForge SQL Complete 0 mentions
  • What if database branching was easy?
    It appears that Datahike [0] is a Datomic workalike that supports branching. I haven’t tried it out myself (yet), but the documentation suggests it’s possible [1]. That said, I’m adding xitdb to the list of tech to try out. Thank you for... - Source: Hacker News / 7 months ago
  • Show HN: Stratum – SQL that branches and beats DuckDB on 35/46 1T benchmarks
    Hey. Hybrid in which sense? I have integrated Stratum's columnar indices as a secondary index in the new query engine of https://github.com/replikativ/datahike itself, so for numerical data you will be able to use Datalog/SQL to have... - Source: Hacker News / 8 months ago
  • The Ten Rules of Schema Growth
    Datahike [0] provides similar functionality to datomic and is open source. It lacks some features however that Datomic does have [1]. [0]: https://github.com/replikativ/datahike. - Source: Hacker News / about 3 years ago

View more

Tracking dbForge SQL Complete since Mar 2021.

Alternatives to Datahike and dbForge SQL Complete

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