Problems Aeca Solves
As services grow, the complexity of data operations and resource demands increase, leading to application performance and scalability difficulties.
Examples:
- RDB: MySQL
- NoSQL: MongoDB
- Cache: Redis
- Analytics: Snowflake, Redshift
- Search: Elastic Search
- Vector DB: Qdrant, Pinecone 등
Aeca: Power in Simplicity
Integrating the necessary data products for application and AI development into a single database, we offer an independent database with comprehensive search capabilities that can be customized to fit business characteristics.
Key Advantages of Aeca
It helps you focus on your business by increasing development productivity.
Single Database
Manage data modeling, search, and caching all in one place.
Huge Data
Process up to 100TB in a single database without distribution.
No Sync
There is no need for synchronization, sharding, and clustering.
No Latentcy
Handle 300,000 queries per second in real time.
(*) when retrieving data from the database
Low Cost
Reduce development expenses including data product usage, server costs, and developer resources by 90% compared to traditional infrastructures.
Quick Dev.
Build and deploy with a minimal development team.
Use Cases
우리는 왜 벡터 검색을 위해 2차원 벡터를 저장하게 되었나?
벡터 임베딩 한계와 특성을 설명하고 이를 저장하기 위한 기능 개선 내용을 다룹니다.
By Finn Choi|2024-07-17
OpenAI는 왜 Rockset을 인수했을까?
2024년 6월 21일 OpenAI는 데이터베이스 스타트업 Rockset 인수를 발표했습니다. OpenAI에 따르면 Rockset 인수의 배경은 AI를 더 유용하게 만들기 위한 검색 인프라 개선이라고 합니다. 구체적으로 어떠한 이점 때문에 OpenAI는 Rockset을 인수했을까요?
By Tim Yang|2024-07-11
판례 데이터를 빠르게 검색 가능한 상태로 만들기
판례 데이터를 다운로드 받고 Aeca를 통해 판례 검색 서비스를 하루만에 구축한 과정을 설명합니다.
By Finn Choi|2024-06-21
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