Kirk Kirkconnell’s Post

We're thrilled to announce the alpha availability of three new features that round out Fauna’s native support for how developers create and manage their database schema across the development lifecycle. Fauna offers development teams a complete set of functionality that supports working with structured and semi-structured data in one model, supports safe data migrations without requiring downtime, and supports the development and deployment of schema with the same tools as application code. 🌟 Schema Enforcement via Document Types Start with schemaless collections and evolve to strict schemas as needed. Schema enforcement via document types allows specifying a collection's set of fields as part of the collection definition. Fauna then enforces that all documents within the collection conform to this defined shape. 🌟 Zero-Downtime Migrations Implement large schema migrations without any service interruptions. Whenever a collection definition changes, Fauna will migrate every existing document in the collection to conform to the new definition. Collection migrations are natively zero-downtime, with no risk of locking up a production database for some indeterminate amount of time. 🌟 Declarative, Schema as Code Migrations Fauna's migration system is integrated with FSL in order to allow you to encode explicit migration steps as part of a collection's definition. In doing so, Fauna preserves the ability to manage your application schema as code while allowing your schema to express more complex migration actions than are possible in a purely declarative approach. Check out the blog for a walk-through of the features, and be sure to register for Early Access if you'd like to get started building with these powerful new features. #serverlessdatabase #distributeddatabase #NoSQL #schema #serverless https://lnkd.in/gKw6YQG8

If you have built and operated an application or service that relies on an operational database in production, you will immediately understand the insane amount of value that these features deliver.

The database market is split into pretty distinct categories: operational, analytical, vector, etc. In the operational category, there are many specialized databases for specific use cases, but the two giant sub-categories are relational and document (it's almost certain you are using one or more of these at your company). Both are great for their respective purposes, however they inevitably come with pretty significant tradeoffs. Relational database users often have to make concessions on flexibility - the ability to iterate a model over time as business requirements change. Document database users often have to make concessions on integrity and relational capabilities - despite most transactional data being relational in nature. I originally joined Fauna a few years ago because I thought it was a very real solution to very real problems and tradeoffs that users of relational or document databases have to constantly factor in when building and scaling an application. A flexible document data model that maintains relational integrity and querying, strongly consistent, etc. Schema is the latest addition to this document-relational story. With Fauna Schema, we're introducing a similar solution to a significant challenge that users of relational and document databases have felt on both sides of the 'schema pain spectrum' - the ability to start schemaless when access patterns are less known (pain for relational DB users), enforce strict schema over time (pain for document DB users), and continue to evolve and migrate as requirements change (pain for everyone). Would love to chat more about this with anyone that's interested in learning more.

With Fauna you can now start with a document model; evolve your application and then enforce schema when you settle on business rules. Do those business rules change? No problem, built in migrations let you move to a new schema with zero downtime. Another cool aspect of this is you can rollout your schema changes using the Fauna Schema Language which you can use in your CI/CD and local development flows like you would with something like liquibase in a relational database.

For the longest time, I've wanted the ability to have a schema in NoSQL databases. In past databases I have worked on, you essentially had to have these controls in your application. What happened when you had multiple apps connecting to your database? "Don't do that. Have one database per app." Or when you start using a NoSQL database, "I don't know my access patterns yet?" Figure it out, get better!! No, I won't help you! This release of Fauna's changes all of that. Start schemaless and add a schema and enforcement gradually over time and we give you tools to help migrate, with zero downtime, from one version of your schema to the next. In addition, you can integrate all of this into git repos and your CI/CD pipelines. Anyhow, if you're developing an app with a database or looking for the kind of controls most modern apps need, now's the time to take a look at Fauna. If you have any questions or need help, you know where to find me.

🚀  We're excited to launch the open beta of Fauna Schema – a comprehensive suite of features that lets development teams define, manage, progressively type, enforce, and seamlessly evolve their database schema. New features include document types and zero-downtime migrations – together bringing full schema enforcement and migrations to Fauna's document model. Fauna Schema solves the challenge of evolving schema on production applications as business requirements change. Traditional databases struggle with schema evolution in the following ways: Document Databases: - Generally bolted-on and rudimentary schema - Single type per field - No type-checking when composing queries - Risk of conflicts and runtime errors Relational Databases: - Inflexible and rigid schema - Limited support for live schema migrations - No gradual typing - Schema changes locking the DB, causing downtime 🌟 Fauna Schema uniquely combines the structure and reliability of relational databases with the flexibility of the document model, boosting development velocity and reducing risk. Start building with Fauna Schema today! Explore more in our launch blog and check out the docs, tutorials, production support registration, and video walk-through in the comments. #DatabaseSchema #NoSQL #BetaLaunch #Serverless https://lnkd.in/gsM2Xz86

✨ Embark on a journey through OceanBase Diagnosis and Tuning series and unleash the potential of OceanBase database✨ Root cause analysis in this native distributed database can be complex and overwhelming for many engineers sometimes. But fear not, as we've got you covered with an enlightening series of articles on the diagnosis and tuning skills with OceanBase. 🎯 In this article, we will dive into the performance view analysis, and learn about the functions and usage instructions of sql_audit. 🔗 Read the article: https://lnkd.in/gkCWKiaq Don't miss this opportunity to upgrade your OceanBase skills and conquer complex database challenges!  #OceanBase  #Database #obdiag

Following up on a previous post, I used knowledge gained at FOSS4G North America to take baby steps toward a Koop provider for DuckDB/GeoParquet. #geospatial #SQL #DuckDB #parquet #geoparquet #cloudnative #datascience

ICYMI - Fauna announced the open beta of Fauna Schema last week! In our latest blog, Principle Database Advocate Kirk Kirkconnell dives deep into some of the new functionality (including document types and zero downtime migrations) that enables development teams to start schemaless and gradually introduce structure as an application evolves. Discover how these advancements can transform your data modeling and performance by bringing together the best of the relational and document worlds. Read the full blog to explore the future of schema with Fauna! #DatabaseSchema #NoSQL #DevTools #BetaLaunch #Serverless https://lnkd.in/gswmPqPQ

#geospatial analysis is the nice mix between real world and 'the matrix' and is packed with valuable use-cases. Entire companies have been built around using and analyzing geospatial data! Why not use postgres to power that? that is the easy question :) Why use a specialized flavor of postgres, and another vendor? - harder question, but the answer is easy, don't...Tembo gives you multi-workload functionality with postgres out of the box...run it in our cloud...or yours!