Pinecone vs. Milvus vs. Qdrant
Introduction The demand for high-performance, scalable vector databases has skyrocketed as artificial intelligence (AI) and
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Category: Database
Scaling Prometheus with Grafana Mimir
Monitoring and observability are critical pillars of modern IT infrastructure. As systems grow in complexity,
Web Crawlers in Search Engines
Search engines are designed with a set of components like crawlers to provide fast responses in web browsers.
Lambda vs. Delta Architecture: An Overview
The Delta Architecture offers more simplicity, quality, and reliability with ACID transactions, compared to other options.
Weaviate Open Source Database for Vector Search
Weaviate is one of the names around vector search engines development. But, what does vector search mean and why is it relevant?
Pinecone Builds Vector Search Platform
According to Pinecone, vector search is the future of online searching and they have built a solution based on artificial intelligence (AI) in the cloud.
PrestoDB and Trino Enhance Open Source Distributed SQL Engine
It seems both PrestoDB and Trino will keep leading the way as the prime Open Source projects for Distributed SQL Engines.
LakeFS Brings Git-like Version Control to Data Lakes
LakeFS brings to the table better manageability for data lakes, without compromising flexibility.
Delta Lake Enables ACID Compliance in Apache Spark
ACID represents a group of guiding principles that should help you make sure database transactions are performed in a reliable manner.
Lambda vs Kappa Architecture
When data processing and data analysis are required, Kappa and Lambda architectures are great options. They can handle both real-time and static datasets, but they do so in very different ways.
Open Source Vector Databases Overview
Vector databases are becoming increasingly important building blocks for machine learning. In this post, we look at some products.
Using Hadoop for Machine Learning
Hadoop is an important building block to some organizations because it’s highly scalable and redundant. Large data volumes can be distributed.