We're doing cool stuff at SurrealDB, and the more we reason about it, the more convenient it would be to have these conversations with a storage person. This is not a single-person position - we consider all applications :) https://lnkd.in/eq_cPSuT If this sounds like you, please drop us a message 🙏 We currently use TiKV and RocksDB for storage but have big plans to improve these implementations to accommodate the surface-level functionality better. #rust #storage #kvstore #database #bigdata
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Are you a software engineer fascinated by the power of Rust and the magic of time series data? I am supporting a team that is leveraging the power of Rust, Apache Arrow and DataFusion to build robust, high-performance storage systems for managing and querying time series data. 🕔 What is time series data? Time series data is a type of data where each data point is associated with a specific timestamp. Time series data is the heartbeat of many modern applications, driving insights and analytics in various fields; some examples include data monitoring & observability metrics, sensor readings, and energy consumption. 🦀 Why Rust, Apache Arrow and DataFusion? Using Rust, Apache Arrow, and DataFusion offers a robust stack for efficient time-series data querying. Rust's performance focus ensures fast, safe execution. Apache Arrow's columnar storage enhances memory efficiency and facilitates cross-language compatibility. DataFusion, built on Arrow, supports parallelized, columnar processing, ideal for analytical queries on large datasets. Feel free to connect and drop me a message if this sounds like an opportunity you'd like to pursue or if you're searching for engineering talent in this area. #rust #timeseriesdata #apachearrow #datafusion
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Rust's error handling is centered around the Result<T, E>, where E typically extends std::error::Error. Here we share our experience organizing variant types of Errors in a complex system, from how an error is defined to how to log the error or present it to end-users. Read here: https://lnkd.in/gUefGbG5 #errorhandling #rustlang #opensource #database #tech
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Liminal Thinker who believes in Observing, Conceptualizing, Contextualizing and then Actualizing all projects. Being Curious and Willing to Learn are my Superpowers, 🤫 Shhh...
Just like bees tirelessly work together to maintain the hive's operations, CockroachDB's highly available design ensures that your mission-critical applications stay online, even during regional outages or database upgrades. It's like having a swarm of dedicated workers ensuring uninterrupted service for your customers. Learn how you can #ScaleWithCockroachDB and keep your business buzzing 👉 www.cockroachlabs.com Cockroach Labs #CockroachDB #Database
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Embarking on a security journey inspired by a pivotal project at work! 🚀 Delving into the intricacies of encrypting Room database with SQLCipher to safeguard sensitive data. Join me in exploring this journey into encrypting Room databases with SQLCipher! https://lnkd.in/ekjvfu6M 🛡️💻 #AndroidDev #DataEncryption #SQLCipher
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Explore "DuckDB, is The Hype Train Behind it Real?" by Gentrit Mehmeti, which delves into the unique adaptability of DuckDB. He explains how DuckDB integrates seamlessly into your applications with a simple installation. The blog highlights DuckDB's fast performance, easy deployment, and compatibility with other databases. Curious about when and how to effectively use DuckDB in your projects? Read the full blog here: https://lnkd.in/deMpRyZB
DuckDB - XponentL Data
xponentl.ai
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Crafting Data Excellence: Empowering organizations with Databricks, AWS, Snowflake and Data Architecture
🚀 Navigating new dependencies in job clusters: Unlike all-purpose compute, where we use a 'lib' tab, setting up a new job cluster requires editing tasks in workflows. 🔄 In the "dependent libraries" in tasks section, add wheel files effortlessly from S3, PyPI, or DBFS. 📦 These dependencies automatically attach to the cluster on launch, streamlining integration. 🚀 I recently explored and found out how to do this, and considering the scarcity of online resources, I wanted to share this valuable insight. Master this process to empower your job clusters with the right tools. 💻✨ #Databricks #JobClusters #TechTips #WorkflowOptimization #Databricksworkflow
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There are other databases in the market, but Greycat is designed to operate over massive datasets efficiently. We’ve tested Greycat v.7’s storage efficiency against Greycat v6 and Postgres. Greycat v7, with its new type decorator @precision, cuts down the dataset’s final disk size in half compared to v6, and down 75% compared to Postgres. Check all details in our Medium post about it here: https://lnkd.in/eTTXqmUU Greycat is a compelling choice for applications requiring efficient storage of large datasets with numerous floating-point values. #DataStorage #BigData #Database #GreyCat #TechInnovation #DataEfficiency #StorageSolutions #TechNews #DataManagement #Medium #Postgres
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“[ScyllaDB is] a much more efficient database — we’re going from running 177 Cassandra nodes to just 72 #ScyllaDB nodes. Each ScyllaDB node has 9 TB of disk space, up from the average of 4 TB per Cassandra node.” Bo Ingram, senior software engineer at Discord. See how combining #Rustlang-based data services and ScyllaDB allowed Discord to build a system that can handle trillions of messages. http://bit.ly/3YLoSwN #NoSQL #NoSQLdatabase
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Tried Writing my first blog regarding Data Science Servers.
Setting Up a Data Science Dedicated Server
link.medium.com
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Let's figure out how we can improve the loading of Postgres extensions (aka PG_FUNCTION_INFO_V2): https://lnkd.in/gd3XJ_dR
PG_FUNCTION_INFO_V2 · pgedc · Discussion #38
github.com
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