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  1. Stackups
  2. Application & Data
  3. Databases
  4. Vector Databases
  5. Epsilla vs Save Ads and Create Viral Video & Image Ads

Epsilla vs Save Ads and Create Viral Video & Image Ads

OverviewComparisonAlternatives

Overview

Epsilla
Epsilla
Stacks0
Followers0
Votes0
GitHub Stars865
Forks42
Save Ads and Create Viral Video & Image Ads
Save Ads and Create Viral Video & Image Ads
Stacks0
Followers2
Votes1

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Detailed Comparison

Epsilla
Epsilla
Save Ads and Create Viral Video & Image Ads
Save Ads and Create Viral Video & Image Ads

It is an open-source, self-hostable vector database for semantic similarity search that specializes in low query latency. It bridges the gap between information retrieval and memory retention in Large Language Models.

Discover, save, download and generate high-performing ads on TikTok, Facebook, YouTube, and more with Ad Library - your all-in-one ad library for winning ads.

High performance and production-scale similarity search for embedding vectors; Full fledged database management system with familiar database, table, and field concepts. Vector is just another field type; Native Python support and REST API interface
Ad Library
Statistics
GitHub Stars
865
GitHub Stars
-
GitHub Forks
42
GitHub Forks
-
Stacks
0
Stacks
0
Followers
0
Followers
2
Votes
0
Votes
1
Integrations
Docker
Docker
Python
Python
No integrations available

What are some alternatives to Epsilla, Save Ads and Create Viral Video & Image Ads?

Milvus

Milvus

Milvus is an open source vector database. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources.

Chroma

Chroma

It is an open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs.

Qdrant

Qdrant

It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.

LanceDB

LanceDB

It is an open-source database for vector search built with persistent storage, which greatly simplifies retrieval, filtering, and management of embeddings.

Lantern

Lantern

It is an open-source PostgreSQL database extension to store vector data, generate embeddings, and handle vector search operations. It provides a new index type for vector columns which speeds up ORDER BY ... LIMIT queries.

Pg_vectorize

Pg_vectorize

It is a Postgres extension that automates the transformation and orchestration of text to embeddings and provides hooks into the most popular LLMs. This allows you to do vector search and build LLM applications on existing data with as little as two function calls.

AthenaDB

AthenaDB

It is a simple, serverless, distributed vector database that can be used as an API. It is designed to handle large amounts of vector text data, making it suitable for projects with high data volumes.

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