We talk about technology challenges, assist in the emergence and development of techniques, popularize solutions in the document database space.
San Francisco, CA
Joined February 2023
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Document Database Community retweeted
FerretDB 2.0, the Truly #opensource MongoDB Alternative is now Generally Available, and recommended for production workloads. Huge thanks to our OSS contributors, early adopters, the Postgres community, and our friends at @Microsoft.
Full announcement: blog.ferretdb.io/ferretdb-v2…
How @LinkedIn Uses NoSQL 🔎
🔗 engineering.linkedin.com/arc…
A case study on how LinkedIn leverages NoSQL databases for scalability and performance.
📚 Distributed Systems for Fun and Profit
🔗 book.mixu.net/distsys/
A free ebook that covers the fundamentals of distributed systems.
🔄 Data Modeling in Machine Learning Pipelines: Best Practices Using SQL and NoSQL Databases
🔗 dataversity.net/data-modelin…
Explore the significance of data management in machine learning workflows and best practices for data modeling using both SQL and NoSQL databases.
⚙️ NoSQL Data Modeling Techniques
🔗 highlyscalable.wordpress.com…
A detailed guide on various data modeling techniques specific to NoSQL databases.
📚 Guide to NoSQL Databases in 2025
🔗 vinova.sg/2025/02/01/guide-t…
In-depth overview of NoSQL databases, discussing their types, advantages, disadvantages, and popular options.
➡️ Open Standards, Licensing, and Open Source
🔗 youtube.com/live/DJIPLRo4Vhs…
📈 SQL and NoSQL Databases Software architectures performance analysis and assessments
🔗 arxiv.org/abs/2209.06977
Systematic literature review analyzing the software architectures of SQL and NoSQL databases, particularly in the context of Big Data processing and cloud environments.
📌 A Taxonomy of Schema Changes for NoSQL Databases
🔗 arxiv.org/abs/2205.11660
⬆️ Generic approach for evolving NoSQL and relational schemas, introducing a taxonomy of schema changes for all U-Schema elements.
✅ Impacts of data consistency levels in cloud-based NoSQL for data-intensive applications
🔗journalofcloudcomputing.spri…
Analysis of various data consistency settings for widely used NoSQL DBMSs, including @MongoDB, @Redisinc, and @cassandra.
🔁 Comparing CosmosDB, DocumentDB, MongoDB, and FerretDB as Document Database for Your Stack
🔗 documentdatabase.org/blog/co…
Dated June, 2023 -> Old but still gold 😎
📍 Microsoft’s new DocumentDB rethinks NoSQL on PostgreSQL
🔗 infoworld.com/article/381263…
Explore Microsoft's latest standalone document-oriented database, offering developers an open-source alternative to MongoDB and potentially setting a new industry standard for NoSQL APIs.
➡️ Best NoSQL Databases for Microservices: Features, Pros, and Cons
🔗 researchgate.net/publication…
This paper analyzes the features, advantages, and drawbacks of databases like @MongoDB and @cassandra, providing insights into their performance, scalability, and applicability in microservices environments.
🎙️ The importance of interoperability and compatibility in database systems
🔗 youtube.com/live/iS45PwK1bZQ…
Database interoperability and compatibility are crucial in today’s cloud-first world. In this session, we’ll discuss how integrating with existing systems and all-in-one cloud offerings (like AI/ML, development, deployment, and storage) drives decisions more than the database itself.
SSPL vs Open Source 🫡
🔗 youtube.com/live/GwwEHyr6CCc…
The “SSPL vs. Open Source” panel is a casual conversation, helping attendees understand the nuanced differences between the Server Side Public License (SSPL) and Open Source Software (OSS), thereby guiding their decision-making processes in software development and deployment.
Too Many Database Types! Which One Should You Pick? 🧐
🔗 medium.com/%40agustin.ignaci…
Look through discussion on various types of NoSQL databases, offering guidance on selecting the appropriate one based on specific use cases.
📹 NoSQL Databases From a Relational Database Admin
🔗 youtube.com/live/zO89_doruEg…
In this session, we'll cover key topics including the basics of NoSQL databases, the pros and cons of SQL versus NoSQL, deployment considerations, data organization, and query optimization strategies.