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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. EuclidesDB vs FaunaDB

EuclidesDB vs FaunaDB

OverviewComparisonAlternatives

Overview

EuclidesDB
EuclidesDB
Stacks0
Followers2
Votes0
GitHub Stars638
Forks31
Fauna
Fauna
Stacks112
Followers153
Votes27

EuclidesDB vs FaunaDB: What are the differences?

EuclidesDB: Machine learning feature database tight coupled with PyTorch. It is a multi-model machine learning feature database that is tight coupled with PyTorch and provides a backend for including and querying data on the model feature space; FaunaDB: The database built for serverless, featuring native GraphQL. FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness and scale. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.

EuclidesDB and FaunaDB can be primarily classified as "Databases" tools.

Some of the features offered by EuclidesDB are:

  • Written in C++ for performance
  • Uses protobuf for data serialization
  • Uses gRPC for communication

On the other hand, FaunaDB provides the following key features:

  • Native support for GraphQL and others. Easily access any data with any API. No middleware necessary.
  • Access all data via a data model that best suits your needs - relational, document, graph or composite.
  • A unique approach to indexing makes it simpler to write efficient queries that scale with your application.

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CLI (Node.js)
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Detailed Comparison

EuclidesDB
EuclidesDB
Fauna
Fauna

It is a multi-model machine learning feature database that is tight coupled with PyTorch and provides a backend for including and querying data on the model feature space.

Escape the boundaries imposed by legacy databases with a data API that is simple to adopt, highly productive to use, and offers the capabilities that your business needs, without the operational pain typically associated with databases.

Written in C++ for performance; Uses protobuf for data serialization; Uses gRPC for communication; LevelDB integration for database serialization; Many indexing methods implemented (Annoy, Faiss, etc); Tight PyTorch integration through libtorch; Easy integration for new custom fine-tuned models; Easy client language binding generation; Free and open-source with permissive license
Native support for GraphQL and others. Easily access any data with any API. No middleware necessary.; Access all data via a data model that best suits your needs - relational, document, graph or composite.; A unique approach to indexing makes it simpler to write efficient queries that scale with your application.; Build SaaS apps more easily with native multi-tenancy and query-level QoS controls to prevent workload collisions.; Eliminate data anomalies with multi-region ACID transactions that don't limit number of keys or documents.; Data-driven RBAC that combines with SSL to offers reliable protection, and yet is simple to understand and codify.; Travel back in time with temporal querying. Run queries at a point-in-time or as change feeds. Track how your data evolved.; Dynamically replicates your data to global locations, so that your queries run fast no matter where your users are.; Easily deploy a FaunaDB cluster on your workstation accompanied by a powerful shell and tools to simplify your workflow.;
Statistics
GitHub Stars
638
GitHub Stars
-
GitHub Forks
31
GitHub Forks
-
Stacks
0
Stacks
112
Followers
2
Followers
153
Votes
0
Votes
27
Pros & Cons
No community feedback yet
Pros
  • 5
    100% ACID
  • 4
    Generous free tier
  • 4
    Removes server provisioning or maintenance
  • 3
    No more n+1 problems (+ GraphQL)
  • 3
    Low latency global CDN's
Cons
  • 1
    Log stack traces to avoid improper exception handling
  • 1
    Must keep app secrets encrypted
  • 1
    Susceptible to DDoS (& others) use timeouts throttling
Integrations
Linux
Linux
Python
Python
LevelDB
LevelDB
PyTorch
PyTorch
macOS
macOS
No integrations available

What are some alternatives to EuclidesDB, Fauna?

MongoDB

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.

MySQL

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

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.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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