Noam Stern

Boost query speed, reduce latency, and enhance cost efficiency without sacrificing accuracy by moving in-memory I/O traffic to SSDs. See how DiskANN is now built into Azure Cosmos DB. #DiskANN https://lnkd.in/evc49kWB

11

Exciting news for Confluent Cloud users: Now you can reset offsets for consumer groups in Confluent Cloud! Check out demo to see how this new feature works and learn how to use it here -> https://cnfl.io/3zRPCoY

56

2 Comments

#MSBuild is here! Check out this blog post for all the details on sessions you can see featuring #AzureCosmosDB! https://lnkd.in/evXbebSM

1

Unlock better observability for your enterprise cloud apps! In our latest blog post, we delve into how #Heroku, paired with New Relic, empowers developers to optimize cloud application performance: https://lnkd.in/gGSfCm7P With robust observability features like application metrics, threshold alerting, and language runtime metrics, you can stay ahead of potential issues and ensure a seamless user experience. Discover best practices for enhancing your cloud applications and learn how to leverage New Relic’s APM capabilities for deeper insights.

53

Learn how to leverage vector search in vCore-based #AzureCosmosDB for #MongoDB for efficient data retrieval and improved performance: https://lnkd.in/guxWj4rr ⚙️💡

1

There are always tradeoffs with databases. #NoSQL and #NewSQL are two that offer expanded capabilities beyond traditional databases. How do the two compare? We analyzed #ScyllaDB and #CockroachDB so you can decide for yourself. https://ow.ly/fRpC50PrP98 #NoSQLdatabase #database

30

1 Comment

Did you know you can use Flink AI in Confluent Cloud to call in external AI models from multiple sources (OpenAI, Vertex AI, Amazon SageMaker, etc.) and use them to easily perform tasks on your Kafka data? Need help getting started? Look no further! In the latest blog from Diptiman Raichaudhuri and Dave Troiano, they walk you through an exercise that takes texts from Amazon Fine Food reviews and gives them a numerical score using an OpenAI GPT-4o classification model, finally displaying them in Kibana. Check it out here ➡️ https://cnfl.io/4ddiczq

186

Next week, we're hosting a live workshop on how to capture DynamoDB change streams into Tinybird. You can register for that workshop here: https://bit.ly/45MqxYf Some context on how that's done: We can use DynamoDB S3 Exports and DynamoDB Streams to capture both historical and change data from DynamoDB and forward it to Tinybird using S3 and Lambda. In this case, a custom Lambda function forwards historical snapshots and change events to Tinybird via the Tinybird's Events API, an HTTP endpoint that easily handles ingestion and write operations to a Tinybird Data Source table. Join the workshop to see how it's done in real-time: https://bit.ly/45MqxYf #DynamoDB #changedatacapture #realtimeanalytics

6

Sr. Product Manager Gahl Levy gives a quick breakdown of the #AzureCosmosDB for #MongoDB architecture options: throughput-based RU/s and vCore. Learn about the benefits of each and when to use which for your workloads. https://lnkd.in/eE--FbCm

3

PostgreSQL continues to evolve with vector search extensions like pgvector and pgvecto. rs. At #P99CONF, benchANT Co-Founder Daniel Seybold will explore recent benchmarks comparing vector search performance across various datasets and configurations, highlighting #PostgreSQL’s adaptability in modern use cases. https://lnkd.in/edejH_fG #ScyllaDB #VectorSearch

19

🎥 New on YouTube: In his 2023 #SAGconf lightning talk Yedidya Schwartz discusses how architectural changes improved application load times by utilizing Redis, AWS Cloudfront, and a microservices architecture, along with observability tools for performance optimization. 👀 Watch now: https://lnkd.in/e9uXrUAr #softwarearchitecture #softwarearchitecturegathering #softwarearchitectureconference #Redis #Microservices #AWSCloudfront

8

🚨 Let's talk Google Cloud storage—because sometimes, it's the little things that make the biggest difference. 🚨 Rearc's Gideon Potok wrote about subtle misconceptions we have around data on GCP, and recommended best practices. This isn't about Filestore vs. Cloud Storage. If you're already there, you've moved beyond blog posts. If you're in the cloud game, it's time to dig deeper. The next level of cloud wisdom lies in rethinking what you know. 💡 Read more here: https://lnkd.in/e8-SapQ2 #Rearc #GCP #CloudStorage

6

💡 Efficient Scaling with #AzureCosmosDB! Learn how dynamic scaling per region & partition adjusts throughput to match real-time workload demands. 🔗 https://lnkd.in/eghN686e

3

The simplest way to manage & organize your Docker images is with a #Docker registry. Starting with a free trial of the JFrog Platform in the #Cloud, you can set up a local, remote & virtual Docker Registry in minutes. Let's get started 👉🏼 https://bit.ly/4cvvcQx

15

JFrog announced a new machine learning (ML) lifecycle integration with MLflow, the open-source platform from Databricks. https://lnkd.in/esaHBnt3 #JFrog #MLflow #MachineLearning #MLOps #DevOps #AI #Datbricks

1

New possibilities! Eliminate issues with fully distributed PostgreSQL from pgEdge. Cloud and on-premises options. Got a minute? Get a demo. https://hubs.ly/Q02zQhHV0 #pgedge #postgresql #postgresqldba #postgresqlprofessionals #multicloud #multiregion

3

Coralogix cut processing times from 30 seconds to 86 milliseconds with a #PostgreSQL to #ScyllaDB migration. Here's how they replaced the original metastore implementation and a breakdown of the lessons they learned. https://ow.ly/GF5850QzCbZ #NoSQL #NoSQLdatabase #database

31