Embeddinghub vs H2O
Overview
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It provides everything you need to develop GPU-accelerated applications
Detailed Comparison
H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark. | It is a database built for machine learning embeddings. It is built with four goals in mind. Store embeddings durably and with high availability, allow for approximate nearest neighbor operations, enable other operations like partitioning, sub-indices, and averaging, and Manage versioning, access control, and rollbacks painlessly. |
| - | Run approximate nearest neighbor lookups, average multiple embeddings, partition tables (spaces), cache locally while training, and more;
Store and index billions vectors embeddings from our storage layer;
Create, manage, and rollback different versions of your embeddings;
Encode different business logic and user management directly into Embeddinghub;
Keep track of how embeddings are being used, latency, throughput, and feature drift over time |
Statistics | |
GitHub Stars 7.3K | GitHub Stars - |
GitHub Forks 2.0K | GitHub Forks - |
Stacks 122 | Stacks 2 |
Followers 211 | Followers 5 |
Votes 8 | Votes 0 |
Pros & Cons | |
Pros
Cons
| No community feedback yet |
Integrations | |
| No integrations available | |
What are some alternatives to H2O, Embeddinghub?
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
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.
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 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
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 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
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 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
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.
