Lambda256’s Post

Syntropy and KYVE Network are bridging the gap between historical and real-time blockchain data 🧗 In our latest case study, learn about the tools and solutions KYVE developed with the Data Layer, making past and present Web3 data accessible 👇

This is my 3rd and final post in a 3-part series on the intersection of AI and blockchain. In this post, I provide examples of how specific blockchains might be used to enable multi-agent AI systems along with a hypothetical real-world healthcare example.

#aipowered Blockchain Data Analytics and MetaData One of the primary challenges confronting Blockchain analytics today lies in keeping pace with the dynamic and evolving blockchain landscape. Transactions are also becoming more complex every day due to the ongoing innovations taking place. Given that the blockchain and #nft industries are still in their early stages, stakeholders anticipate this challenge to intensify with time. To effectively make sense of these obstacles, and navigate them, analytics initiatives can tap into the wealth of data available within the bitsCrunch networks. bitsCrunch network undergoes continuous enrichment through contributions from the community, ensuring it continues to align with the latest developments in the blockchain space. By harnessing this ever-evolving data source, #blockchainAnalytics projects can concentrate their efforts on furnishing valuable insights to their clientele while staying abreast of the rapid changes in the industry.

#Syntropy's Data Layer utilizes an exceptional blend of technologies to simplify the retrieval and utilization of on-chain data. Central to this layer are dynamic data streams, delivering a steady stream of information directly from the most prominent #blockchains worldwide. #blockchain #web3 #DePIN https://lnkd.in/dHyBm4dg

"By visualizing data streams in real time, we can move beyond the limitations of databases and data lakes of the past and race into a world where we can query the future. Imagine this: Seeing live Ethereum transactions as they happen, tracking suspicious patterns, or even tracing the flow of funds from one account to another— all in real time — gives you the power to shift from reactive to proactive decision-making." Read more by Matthew Pagan (aka MattDott) on how #Quine & #GraphXR form a powerful duo for working with streaming data, enabling real-time analysis and visualization of complex datasets such as the Ethereum blockchain: https://lnkd.in/eTS-abcQ Kineviz | thatDot #streamingdata #Ethereum #blockchain #datavisualization #graphanalytics #realtimeanalysis

🚀 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 𝗶𝗻 𝗠𝗮𝘀𝘀𝗮 𝗦𝗺𝗮𝗿𝘁 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝘀 🚀 Did you know that all data stored on the blockchain in Massa is handled as raw bytes? 🧩 This ensures high efficiency, but it requires us to serialize everything before storing it. Fortunately, the Massa SDK simplifies this process, allowing developers to work with familiar data types like 𝘀𝘁𝗿𝗶𝗻𝗴, 𝗔𝗿𝗴𝘀, and 𝗦𝘁𝗮𝘁𝗶𝗰𝗔𝗿𝗿𝗮𝘆<𝘂𝟴> without manually converting them to bytes. Here’s a breakdown of how it works: 🔹 𝗦𝘁𝗼𝗿𝗶𝗻𝗴 𝗦𝗶𝗺𝗽𝗹𝗲 𝗗𝗮𝘁𝗮: If you want to store an integer or text, convert it to a string first. let balance: i32 = 150; Storage.set("user_balance", balance.toString()); // Convert to string before storage 🔹 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗶𝗻𝗴 𝗗𝗮𝘁𝗮: When retrieving data, parse it back to the original type: let balanceStr = Storage.get("user_balance"); let balance = balanceStr !== null ? I32.parseInt(balanceStr) : 0; 🔹 𝗦𝘁𝗼𝗿𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝗹𝗲𝘅 𝗗𝗮𝘁𝗮 𝘄𝗶𝘁𝗵 𝗔𝗿𝗴𝘀: For more complex structures, like a user’s profile with a name and age, the Args type allows easy serialization: let profile = new Args(); profile.add("Bob").add(30); // Add name and age Storage.set("user_profile", profile.serialize()); // Store serialized profile 🔹 𝗦𝘁𝗼𝗿𝗶𝗻𝗴 𝗥𝗮𝘄 𝗕𝘆𝘁𝗲𝘀 𝘄𝗶𝘁𝗵 𝗦𝘁𝗮𝘁𝗶𝗰𝗔𝗿𝗿𝗮𝘆<𝘂𝟴>: For raw binary data, StaticArray<u8> allows you to store fixed-size byte arrays efficiently: let rawData: StaticArray<u8> = new StaticArray<u8>(3); rawData[0] = 0x01; rawData[1] = 0x02; rawData[2] = 0x03; Storage.set("raw_data", rawData); // Store raw byte data 𝗧𝗵𝗶𝘀 𝘀𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲𝗱 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗺𝗮𝗸𝗲𝘀 𝗱𝗮𝘁𝗮 𝗯𝗼𝘁𝗵 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝘁𝗼 𝘀𝘁𝗼𝗿𝗲 𝗮𝗻𝗱 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿-𝗳𝗿𝗶𝗲𝗻𝗱𝗹𝘆 𝘁𝗼 𝘄𝗼𝗿𝗸 𝘄𝗶𝘁𝗵! 🎉  By handling the serialization internally, the Massa SDK provides a flexible and intuitive way to manage blockchain data. 📈 For more information check out the doc: https://lnkd.in/ep5Z66we #MassaLabs #Blockchain #SmartContracts #AssemblyScript #Storage #Web3 #BlockchainDevelopment #DeveloperTips

Ormi: Revolutionizing Blockchain Data Management with a Three-Pillar Approach In the ever-evolving world of Web3, managing the vast amounts of data generated by blockchains, layer 2 solutions, and decentralized applications has become a formidable challenge. At Ormi, we are tackling this head-on with our innovative three-pillar approach and groundbreaking products, designed to provide real-time, petabyte-scale access to blockchain data. 🔍 The Problem: Overwhelming Web3 Data The Web3 ecosystem faces several critical issues: - Fragmented Ecosystems: Layer 2 and 3 solutions and rollups generate immense transaction data, often reaching up to 1 petabyte, overwhelming standard databases and cloud solutions. - Gazillion Data Volume: Managing archival nodes across 100 chains is a monumental task, with data extraction taking months. - Redundant, Brittle Architecture: Redundant creation of Web3 data models by various internal stacks, with no standardization, despite universal application needs. 🚀 The Solution: Ormi’s Unified Data Layer for Web3 Ormi addresses these challenges with three cutting-edge products: 1) 0xgraph: Our next-gen data API, fully compatible with The Graph, is optimized for real-time, edge data access, enhancing critical DeFi experiences. > Hosts 500 subgraphs (25% of The Graph's total) > Built on Ormi's metal cloud > 3x faster sync speed and 1.5x better data compression > Average 24ms response time at 1k req/s, 3x faster than competitors 2) 0xdb: A robust blockchain SQL data engine providing the industry's fastest indexing at 17 billion rows/hour. >Custom sync, transformation, and data pipeline capabilities >20x faster historical data syncing than Geth clients >3x faster query speed than Dune >Stores over 500TB of blockchain data models >Optimized for ML, AI, Quant, and Algo trading 3) 0xintel (TBA): Utilizing graph machine learning and AI, built on the high-performance 0xdb engine, to democratize access to blockchain intelligence. >Designed for compliance, risk scoring, entity clustering, AML, and Sybil defense >Detected over 97,000 entities, labeled 1,400,000 addresses, generated 5,900 behavior labels, identified 195,000 tokens, and detected 11,000+ protocols and 50,000 contracts across 12 blockchains #Blockchain #Web3 #Onchaindata #DeFi #ETL #BigData

How about visualizing Blockchain ledger data with GraphQL instead of SQL-like queries? GraphQL queries are designed to fetch the exact data without overfetching. They operate on the standard HTTP protocol instead of the specific database-driven connection, making them easily accessible from web applications. Here is how you can use Bitquery to fetch and visualize Blockchain data from over 30 Blockchain networks. https://lnkd.in/gzhbgsRW #UseCase #Visualization #Blockchain 

Syntropy January Monthly Update: Silverstone in Full Swing ✔️the initiation of MetaMask integration on the testnet, ✔️ #Syntropy 101 breaks down the Data Layer ✔️Partnership with Morpheus AI ✔️Unpacking #RPCs, #APIs, and real-time data ✔️The Data Layer and #DePIN https://lnkd.in/dnm7vxjb #blockchain #web3 #blockchaintech #blockchaintechnology