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

EuclidesDB vs LeanXcale

OverviewComparisonAlternatives

Overview

EuclidesDB
EuclidesDB
Stacks0
Followers2
Votes0
GitHub Stars638
Forks31
LeanXcale
LeanXcale
Stacks1
Followers4
Votes0

EuclidesDB vs LeanXcale: What are the differences?

Developers describe EuclidesDB as "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. On the other hand, LeanXcale is detailed as "A scalable SQL database with fast NoSQL data ingestion and GIS capabilities". It is a scalable SQL database with fast NoSQL data ingestion and GIS capabilities. It simplifies your architecture thanks to its combination of SQL and NoSQL capabilities. Move faster from customer needs detection to production avoiding complex architectures such as lambda. Development is made easy using the SQL API.

EuclidesDB can be classified as a tool in the "Databases" category, while LeanXcale is grouped under "SQL Database as a Service".

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, LeanXcale provides the following key features:

  • Rapid data ingestion
  • Powerful SQL & GIS
  • Linear scalability

EuclidesDB is an open source tool with 597 GitHub stars and 26 GitHub forks. Here's a link to EuclidesDB's open source repository on GitHub.

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Detailed Comparison

EuclidesDB
EuclidesDB
LeanXcale
LeanXcale

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.

It is a scalable SQL database with fast NoSQL data ingestion and GIS capabilities. It simplifies your architecture thanks to its combination of SQL and NoSQL capabilities. Move faster from customer needs detection to production avoiding complex architectures such as lambda. Development is made easy using the SQL API.

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
Rapid data ingestion; Powerful SQL & GIS ; Linear scalability
Statistics
GitHub Stars
638
GitHub Stars
-
GitHub Forks
31
GitHub Forks
-
Stacks
0
Stacks
1
Followers
2
Followers
4
Votes
0
Votes
0
Integrations
Linux
Linux
Python
Python
LevelDB
LevelDB
PyTorch
PyTorch
macOS
macOS
.NET
.NET
Apache Spark
Apache Spark
Python
Python
Kafka
Kafka
Java
Java
Linux
Linux
Windows
Windows

What are some alternatives to EuclidesDB, LeanXcale?

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.

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

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.

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