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The most powerful SQLite database is a Cloudflare Developers Durable Object with row level security, query allowlist, data masking, REST API, web sockets + query caching. Today we're announcing Auth + RLS + Allowlist + Query Caching are available by default in StarbaseDB. Read more 🧵

Brayden

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20,431 views • 1 year ago •via X (Twitter)

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Brayden Wilmoth1 year ago

StarbaseDB: Allowlist + RLS + Auth Example: Blog Post:

Brayden Wilmoth1 year ago

1. Query Caching Any request you make to your instance with the header "X-Starbase-Cache" in it will now automatically be cached for 60 seconds. Perfect for external data source use cases where connecting to Postgres, MySQL, Mongo or others and you want your data response cached on the edge. Early testing shows multi-second SQL requests going down to as little as ~50ms! Few caveats exist here including: - Response cached must be less than 1MiB (RPC restriction in Workers) - Query must not contain any modifying statements (SELECT only) - No dynamic parameters Many improvements to come here to improve all three of the above areas.

Brayden Wilmoth1 year ago

2. Allowlist You can now specify a specific list of queries that can be executed against your external data source to prevent users from trying to access data tables they shouldn't. This works when connecting StarbaseDB to other database viewers, or by hitting the endpoints your instance exposes. This feature is an essential piece to the puzzle for enabling executing SQL statements safely from the frontend and keeping security at the forefront.

Brayden Wilmoth1 year ago

3. Row Level Security A feature that is mostly touted as a core part of Postgres but always recommended to have a secondary layer in your application logic. Now as part of StarbaseDB it comes built in out of the box so you can define table policies that should exist. You can now query "SELECT * FROM todos;" and by design only get the todos that are relevant to the requesting user. When a policy exists on a table that indicates that RLS is turned "on" for that entire table. You can easily create rules for what operations can be performed. Again, another very important piece to the SQL from frontend goal. This feature is still in Early Access but want to give everyone the opportunity today to start working with it and providing feedback to us on how it should improve.

Brayden Wilmoth1 year ago

Lastly, all of this is still in EARLY ACCESS! More to come but we want to get this into peoples hands early and invite feedback. There will be quirks, limitations, and gotcha's I'm sure. The foundation has been set and now it is time for us to build & improve what we have. 🙏🚀

Sandrino Di Mattia1 year ago

@CloudflareDev What are your thoughts on cost? Each time you query the DB it will count as 1 worker invocation, right?

Brayden Wilmoth1 year ago

@CloudflareDev 15,000,000 requests for $8 is a good problem to have in my books.

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109,517 views • 1 year ago

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The Graph’s Sunrise of Decentralized Data is here 🌅 The hosted service has officially upgraded to The Graph Network, now the exclusive home of The Graph’s data services. Experience web3 data with ultra-fast syncing, reliable uptime, global redundancy and much more – all secured by decentralization. With support for over 50 chains, 6,000+ subgraphs on the network and available to query, and many new developer experience-enhancing features, anyone can easily tap into the network’s best-in-class performance. Thousands of dapps and teams like Aave, Art Blocks, Balancer, Snapshot, Decentraland, ens.eth, Lido, Messari by Blockworks, PancakeSwap, and Sushi.com already rely on the network, which has successfully served billions of high-quality queries per quarter across thousands of subgraphs. The Graph’s decentralized model allows web3 developers to build confidently, knowing they are leveraging a scalable data layer to meet the industry’s growing activity. The future of web3 is built on The Graph.

The Graph

100,424 views • 2 years ago

We sit down with Rodrigo Coelho CEO of Edge & Node working on The Graph The Graph is the indexing and querying backbone for Web3, empowering dApp developers by solving blockchain data bottlenecks. They are a decentralized protocol for indexing and querying blockchain data—think of it as the Google of Web3. 🇦🇷 Rodrigo shares compelling real-world crypto use cases (like surviving inflation in Argentina at 1000% a year). ⛓️ Importance of decentralization where Apps don't rely on centralized servers to query data, introducing a single point of failure. 🧑‍🔬 His vision of Web3 as a truly global, inclusive, and unstoppable force. His big message: "We index everything so builders can build anything." Guest: Rodrigo Coelho Host: ᗩｖ𝔦 🥞 OOO: Jody Flournoy 🥞 | Sean Ristau 🥞

We sit down with Rodrigo Coelho CEO of Edge & Node working on The Graph The Graph is the indexing and querying backbone for Web3, empowering dApp developers by solving blockchain data bottlenecks. They are a decentralized protocol for indexing and querying blockchain data—think of it as the Google of Web3. 🇦🇷 Rodrigo shares compelling real-world crypto use cases (like surviving inflation in Argentina at 1000% a year). ⛓️ Importance of decentralization where Apps don't rely on centralized servers to query data, introducing a single point of failure. 🧑‍🔬 His vision of Web3 as a truly global, inclusive, and unstoppable force. His big message: "We index everything so builders can build anything." Guest: Rodrigo Coelho Host: ᗩｖ𝔦 🥞 OOO: Jody Flournoy 🥞 | Sean Ristau 🥞

21Rates

25,971 views • 1 year ago

One of our most powerful features is 'fee delegation' - a protocol that removes the need for enterprises to manage transaction fees and a key step towards mass adoption of blockchain technology. We've just implemented fee delegation in our Web Wallet - - providing developers with powerful capabilities by removing the need for users to pay gas fees. Blockchain adoption depends on its ease of use. By creating a seamless user experience, #vechain is building the platform that onboards the next billion users. Alongside our upcoming #Web3-as-a-service platform, VORJ, and implementation of popular #Ethereum tools and standards, we're building the ultimate environment for #dapps, #DeFi, and the incoming tidal wave of Web2 user adoption. We're building the future - are you? Read about our VeWorld upgrade here:

One of our most powerful features is 'fee delegation' - a protocol that removes the need for enterprises to manage transaction fees and a key step towards mass adoption of blockchain technology. We've just implemented fee delegation in our Web Wallet - - providing developers with powerful capabilities by removing the need for users to pay gas fees. Blockchain adoption depends on its ease of use. By creating a seamless user experience, #vechain is building the platform that onboards the next billion users. Alongside our upcoming #Web3-as-a-service platform, VORJ, and implementation of popular #Ethereum tools and standards, we're building the ultimate environment for #dapps, #DeFi, and the incoming tidal wave of Web2 user adoption. We're building the future - are you? Read about our VeWorld upgrade here:

VeChain

198,192 views • 3 years ago

Everything you ever wanted to know about ClickHouse but were afraid to ask... I interviewed the creator and CTO of ClickHouse, Alexey Milovidov and we discuss: • Why AI companies like OpenAI are adopting ClickHouse • How its architecture has evolved since 2009 • How ClickHouse leverages Bayesian statistics for kernel instruction set optimization • Where ClickHouse positions itself in the data landscape (LanceDB, MinIO , Iceberg) • What Alexey thinks about other OLAP database technologies (spoiler alert: he was complimentary) • ClickHouse features like vector data types, hyperloglog / data sketches, replacing ZooKeeper with ClickKeeper, writing a Apache Calcite-like query optimizer / analyzer from scratch • How ClickHouse Cloud balances the needs of its paying customers and 1000s of open source community members ... and much, much more. The link to the interview and full transcript is in the replies.

Everything you ever wanted to know about ClickHouse but were afraid to ask... I interviewed the creator and CTO of ClickHouse, Alexey Milovidov and we discuss: • Why AI companies like OpenAI are adopting ClickHouse • How its architecture has evolved since 2009 • How ClickHouse leverages Bayesian statistics for kernel instruction set optimization • Where ClickHouse positions itself in the data landscape (LanceDB, MinIO , Iceberg) • What Alexey thinks about other OLAP database technologies (spoiler alert: he was complimentary) • ClickHouse features like vector data types, hyperloglog / data sketches, replacing ZooKeeper with ClickKeeper, writing a Apache Calcite-like query optimizer / analyzer from scratch • How ClickHouse Cloud balances the needs of its paying customers and 1000s of open source community members ... and much, much more. The link to the interview and full transcript is in the replies.

Michael E. Driscoll

17,736 views • 1 year ago

The future of writing database queries is not writing them at all! MongoDB just released their own MCP Server, and it quietly shifts how we interact with databases. It connects to AI tools like Claude, Cursor, or GitHub Copilot, and you can just talk to your database using natural language: → "What's the schema for the orders collection?" → "Find the top 10 users by purchase volume." → "Create a read-only DB user." No need to context switch. No need to memorize query syntax. No need to even leave your IDE. It works across MongoDB Atlas, Community, and Enterprise, and supports admin ops, schema exploration, indexing, and code generation, all via natural language. This way, you can focus on what actually matters: data modeling, app logic, and product experience. Link to the announcement in the next tweet. Thanks to #MongoDB team for partnering with me today!

The future of writing database queries is not writing them at all! MongoDB just released their own MCP Server, and it quietly shifts how we interact with databases. It connects to AI tools like Claude, Cursor, or GitHub Copilot, and you can just talk to your database using natural language: → "What's the schema for the orders collection?" → "Find the top 10 users by purchase volume." → "Create a read-only DB user." No need to context switch. No need to memorize query syntax. No need to even leave your IDE. It works across MongoDB Atlas, Community, and Enterprise, and supports admin ops, schema exploration, indexing, and code generation, all via natural language. This way, you can focus on what actually matters: data modeling, app logic, and product experience. Link to the announcement in the next tweet. Thanks to #MongoDB team for partnering with me today!

Akshay 🚀

32,084 views • 11 months ago

A DEVELOPER FOUND SEVEN WAYS TO TAKE DOWN A PRODUCTION DATABASE THAT ALL LOOK EXACTLY LIKE NORMAL, INNOCENT CODE AND ALMOST EVERY TEAM IS SHIPPING AT LEAST ONE OF THEM RIGHT NOW 17 minutes from Josh Berkus, one of the people who actually maintains PostgreSQL, walking through the quiet mistakes that turn a healthy database into a 3am outage. -> The moment it lands, you realize none of these are exotic attacks. They're ordinary-looking decisions -- a query that locks a table, a connection that never closes, a setting no one ever questioned -- that work perfectly until the day they don't, and then they take everything down with them. The scary part isn't that the database breaks. It's how normal the code looks right up until it does. A query that runs in 5ms on your laptop and 5 minutes on prod. A migration that silently locks the whole table. A connection pool that runs dry the moment real traffic shows up. Every one of them passed review. Writing SQL that runs was never the hard part -> writing SQL that survives production is. And now that an AI agent is generating and firing queries at your real database faster than anyone can read them, every one of those seven landmines is one autocomplete away -- and the only person who can stop it is the one who already knows where they're buried. Your database doesn't go down because someone attacked it. It goes down because something that looked completely normal finally caught up with it. Save and Watch it today. You'll see the next outage coming before it lands ↓

A DEVELOPER FOUND SEVEN WAYS TO TAKE DOWN A PRODUCTION DATABASE THAT ALL LOOK EXACTLY LIKE NORMAL, INNOCENT CODE AND ALMOST EVERY TEAM IS SHIPPING AT LEAST ONE OF THEM RIGHT NOW 17 minutes from Josh Berkus, one of the people who actually maintains PostgreSQL, walking through the quiet mistakes that turn a healthy database into a 3am outage. -> The moment it lands, you realize none of these are exotic attacks. They're ordinary-looking decisions -- a query that locks a table, a connection that never closes, a setting no one ever questioned -- that work perfectly until the day they don't, and then they take everything down with them. The scary part isn't that the database breaks. It's how normal the code looks right up until it does. A query that runs in 5ms on your laptop and 5 minutes on prod. A migration that silently locks the whole table. A connection pool that runs dry the moment real traffic shows up. Every one of them passed review. Writing SQL that runs was never the hard part -> writing SQL that survives production is. And now that an AI agent is generating and firing queries at your real database faster than anyone can read them, every one of those seven landmines is one autocomplete away -- and the only person who can stop it is the one who already knows where they're buried. Your database doesn't go down because someone attacked it. It goes down because something that looked completely normal finally caught up with it. Save and Watch it today. You'll see the next outage coming before it lands ↓

slash1s

22,268 views • 1 month ago

Database table size impacts performance in more ways than one: a) B-tree depth. Using 8k pages and a 16b uuid: 1 level = ~370 rows 2 levels = ~138k rows 3 levels = ~50m rows 4 levels = ~20b rows The lookup cost on a table with 100k rows is not the same as one with 1b rows. This can apply both to the table itself (MySQL cluster index) as well as the indexes. Sometimes a single query requires many of them. b) Small table → fits in RAM → fast reads. The larger the table, the more likely to read from disk plus churn the cache. c) # of indexes. Each adds maintenance overhead for insertions, and for Postgres vacuum overhead as well. Keep an eye on this! It's useful to take regular stock of your tables + indexes. Clean bloat. Remove unused indexes. Partition if needed.

Database table size impacts performance in more ways than one: a) B-tree depth. Using 8k pages and a 16b uuid: 1 level = ~370 rows 2 levels = ~138k rows 3 levels = ~50m rows 4 levels = ~20b rows The lookup cost on a table with 100k rows is not the same as one with 1b rows. This can apply both to the table itself (MySQL cluster index) as well as the indexes. Sometimes a single query requires many of them. b) Small table → fits in RAM → fast reads. The larger the table, the more likely to read from disk plus churn the cache. c) # of indexes. Each adds maintenance overhead for insertions, and for Postgres vacuum overhead as well. Keep an eye on this! It's useful to take regular stock of your tables + indexes. Clean bloat. Remove unused indexes. Partition if needed.

Ben Dicken

211,974 views • 3 months ago