Jon Haddad

Learn about the evolution of the Elasticsearch .NET client and how it will gradually phase out the old NEST library: https://gag.gl/tCCrQX #ElasticSearchLabs

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Developers love Redis because it’s fast. Liftoff uses Redis Cloud as a high-availability, low-latency database, increasing their ROI by improving ad relevance and quality. Hear more about the benefits of their improved ad relevance and quality straight from the director of engineering at Liftoff Mobile. Learn more about Liftoff's soaring ad exchange with Redis Cloud's low latency: https://lnkd.in/gAWBScEk

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Pretty cool to see those benchmarks! I hope one day MySQL goes even further allowing to disable logging for some tables as PostgreSQL does (and empty those tables on unclean restart) https://lnkd.in/eugs9iFu #mysql #innodb #postgres

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👋 🛠️ Say goodbye to complex troubleshooting. With Synthia, the AI assistant built into Sisense's Compose SDK, developers get real-time guidance—no technical jargon needed. Whether you’re a seasoned coder or new to the game, Synthia makes navigating Compose SDK seamless, solving challenges and optimizing workflows faster. Start your 30-day free trial 👉 https://bit.ly/4dGzK7j #AI #SaaS #DataScience

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new post - we chatted with Davis Liang) about some of the engineering challenges and breakthroughs for a company training their own healthcare LLMs -dealing with multiple languages -handling model drift -generalist models vs. healthcare specific ones and more. You can read it here: https://lnkd.in/dgmZY35G (just fyi, this one is a sponsored post but it's pretty interesting if you're interested in healthcare-specific LLMs)

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Now that #Pentaho is no longer available as open source, what are your options? 💰 you have too much money and buy an enterprise license for a platform that no longer evolves ⏰ do nothing and wait until your production runs start to fail OR.... 🚀 upgrade your Pentaho projects to #ApacheHop ☘️ Apache Hop started as a fork of #PDI back in 2019. A lot has changed under the hood since then, but migrating to Apache Hop is still straightforward. All of your jobs and transformations can be converted to workflows and pipelines, and benefit from all of the new functionality in Apache Hop. Check out the 7 key points to upgrade your Pentaho project to Apache Hop, and reach out if you'd like to learn more about Apache Hop, or if you'd like to learn how upgrading can be the perfect way forward for your Pentaho project!

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Join me next week to learn more about indexing in #PostgreSQL. It's not just about B-Tree indexes. 😉

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Join me next week for a discussion about table partitioning at the inaugural 🐘 Postgres Meetup for All 🐘 virtual meetup. We'll talk about partitioning basics, the why and how, and even a few things that recent versions of Postgres have improved. https://buff.ly/4eRUJUU The goal for "Postgres Meetup for All" is to provide not only a variety of speakers and topics, but time for discussion and interaction. I'm planning on a round of introductions from attendees, a short presentation (20-30 minutes), and then discussion time. If you're thinking about table partitioning, working through issues, or even have some tips of your own to share, join us for this discussion.

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See how simple it is to create chatbots with Microsoft Azure On Your Data and vector embeddings from an existing Elasticsearch index: https://lnkd.in/gBHZbkjq #ElasticSearchLabs #RAG #VectorDatabase

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See how the #ElasticSeachLabs team is optimizing scalar quantization for vector databases, unlocking performance gains for int4 quantization in Lucene: https://lnkd.in/eDUFF5_q #VectorDatabase #Lucene

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Your Datalake - in 2024 don't just consider the job done with Iceberg-ing and Object Storage-ing . Take a look at Apache Doris. We are coming full circle where 'integrated solutions' such as Clickhouse and Apache Doris are capable of doing the heavy lifting. They even include features such as federated querying. Apache Doris is my current favourite. This article by Dien, Tran Thanh gives you a great inside look into a migration from BigQuery to Apache Doris. https://lnkd.in/eGYbvCKx

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Confluent's Tableflow is getting closer and closer to GA. Materializing Kafka topics as Iceberg tables, but with a great deal of thought around schema conversion, schema evolution and such. It's amazing how much work goes into making a product robust to schema changes. After the initial announcement I wrote two articles explaining Tableflow and its role in the future of bringing operational and analytics planes together. * Tableflow: the stream/table, Kafka/Iceberg duality: https://lnkd.in/gZbQ2cZ8 * Hybrid Transactional/Analytical Storage: https://lnkd.in/dTg6DKVy

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Really excited about the 'Hudi-rs' release 🎉 Not every data workload requires the need for distributed processing and to setup Spark & JVM to execute them. In fact, there has been an increasing trend in terms of using Rust & Python-based compute engines for a range of workloads. The hudi-rs project is a native Rust library for Apache Hudi, with bindings into Python. This opens up an exciting new world where users can read Hudi tables using non-JVM compute engines. Under the hood, hudi-rs uses #ApacheArrow. So, it scans the Hudi table and reads out records as Arrow RecordBatch. RecordBatch is a table-like data structure that is semantically a sequence of fields, each a contiguous Arrow Array. Once the records are in an Arrow Table, you can easily use it with Arrow-native and integrated tools such as DuckDB, Polars, Daft etc. for further analysis. This is an exciting new direction for open lakehouse platforms like Hudi that brings differentiating capabilities such as: incremental processing, multi-modal indexing subsystem, open table services, among others. We would also love to have any sort of community contributions & PRs. Check out the contributing link & repo in comments. #dataengineering #softwareengineering

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Teaching a workshop on this tomorrow at FedGeoDay. Let me know if you want me to deliver a customized or standard version at your company. We go all the way from unstructured data to vector similarity search combined with #postgis. Get hands on with some of the latest tech in AI

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Why should you test your IaC? And how does the #Terraform Test Framework compare to Terratest? Here's everything you need to know 👇

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💡 Optimizing Costs with Dragonfly: A Technical Breakdown 💻 For technical teams looking to maximize performance while minimizing cloud infrastructure costs, Dragonfly offers significant advantages. By cutting down memory overhead, leveraging CPU-specific optimizations, and using a shared-nothing architecture, Dragonfly is designed to be resource-efficient while maintaining high throughput. Whether you’re scaling horizontally or aiming to optimize performance, Dragonfly can help you reduce operational costs without sacrificing speed. In this blog, we break down the technical strategies that Dragonfly uses to cut costs and improve efficiency. 🔗 Read more here: https://hubs.la/Q02RDNVr0 #CloudOptimization #TechEfficiency #DevOps #DatabasePerformance #Dragonfly#CostReduction

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