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Heroic vs Lovefield

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Heroic
6
23
+ 1
0
Lovefield
2
27
+ 1
3
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Heroic vs Lovefield: What are the differences?

Developers describe Heroic as "A scalable time series database based on Cassandra and Elasticsearch, by Spotify". Heroic is Spotify's in-house time series database. It was built to address the challenges Spotify was facing with near real-time data collection and presentation at scale. On the other hand, Lovefield is detailed as "A relational database for web apps, by Google". Written in JavaScript, works cross-browser. Provides SQL-like APIs that are fast, safe, and easy to use.

Heroic and Lovefield belong to "Databases" category of the tech stack.

Heroic and Lovefield are both open source tools. It seems that Lovefield with 6.11K GitHub stars and 383 forks on GitHub has more adoption than Heroic with 710 GitHub stars and 89 GitHub forks.

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Pros of Heroic
Pros of Lovefield
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    • 2
      Relational database
    • 1
      No servers

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    Cons of Heroic
    Cons of Lovefield
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      • 1
        Limited memory store

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      What is Heroic?

      Heroic is Spotify's in-house time series database. It was built to address the challenges Spotify was facing with near real-time data collection and presentation at scale.

      What is Lovefield?

      Written in JavaScript, works cross-browser. Provides SQL-like APIs that are fast, safe, and easy to use.

      Need advice about which tool to choose?Ask the StackShare community!

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      What companies use Heroic?
      What companies use Lovefield?
        No companies found
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        What tools integrate with Heroic?
        What tools integrate with Lovefield?
          No integrations found
          What are some alternatives to Heroic and Lovefield?
          navi
          It allows you to browse through cheatsheets (that you may write yourself or download from maintainers) and execute commands, prompting for argument values.
          Just
          It is a build task definition library. It stands on the shoulders of two excellent and well tested libraries: undertaker and yargs. It also provides what we call "stacks" to complete the workflow of building a repository.
          MySQL
          The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
          PostgreSQL
          PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
          MongoDB
          MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
          See all alternatives

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