nodejs-bigquery
nodejs-pubsub
nodejs-bigquery | nodejs-pubsub | |
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43 | 24 | |
457 | 512 | |
0.9% | 0.4% | |
8.0 | 8.4 | |
2 days ago | 5 days ago | |
TypeScript | TypeScript | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
nodejs-bigquery
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Wrangling BigQuery at Reddit
If you've ever wondered what it's like to manage a BigQuery instance at Reddit scale, know that it's exactly like smaller systems just with much, much bigger numbers in the logs. Database management fundamentals are eerily similar regardless of scale or platform; BigQuery handles just about anything we throw at it, and we do indeed throw it the whole book. Our BigQuery platform is more than 100 petabytes of data that supports data science, machine learning, and analytics workloads that drive experiments, analytics, advertising, revenue, safety, and more. As Reddit grew, so did the workload velocity and complexity within BigQuery and thus the need for more elegant and fine-tuned workload management.
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Building a dev.to analytics dashboard using OpenSearch
Now I know I've got some data I could use, I now need to find a platform that I can use to analyse the data coming from the Forem API. I did consider some other pieces of software, such as Google BigQuery (with looker studio) and ElasticSearch (with Kibana), I ultimately went with OpenSearch which is essentially a forked version of ElasticSearch maintained by AWS. The main reasons are that I could host it locally for free (unlike BigQuery). I do have some prior experience with both elastic (back when it was called ELK) and OpenSearch, but my work with OpenSearch was far more recent, so I decided to go with that.
- Como evitar SQL Injection utilizando client do BigQuery
- Learning Excel. Is there a resource for fake data sets like retail and wholesale inventories and sales histories etc for testing and practice?
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How to Totally Fubar Your Cloud Infrastructure Costs
First, in one of our recent projects, we helped our client to run the cloud-based infrastructure of their entirely automated, real-time SEO platform. The solution rested in the safe familiarity of Google’s popular cloud-based data centres (i.e. Google Cloud Platform), whilst also making use of BigQuery — a serverless, multi-cloud data warehouse.
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Data Analytics at Potloc I: Making data integrity your priority with Elementary & Meltano
Bigquery as our data warehouse
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I've tried really hard but need some help please. Bigquery not returning data after 2019.
This post in github thinks it may be an error in bigquery's backend.
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Deploying a Data Warehouse with Pulumi and Amazon Redshift
A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of data-warehouse products include Snowflake, Google BigQuery, Azure Synapse Analytics, and Amazon Redshift — all of which, incidentally, are easily managed with Pulumi.
- [Question] Which GCP tool should I use to build a Business decisional dashboard?
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Designing a Video Streaming Platform 📹
Google BigQuery
nodejs-pubsub
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Event-Driven Architecture 101
Secondly, Go is incredibly easy to learn and in my opinion, maintain. This means that if you're a growing company and expect to onboard new teams and team members, having Go as a basis for your systems should mean that new engineers can get up to speed quickly. Below is a small sample application that can connect to Google PubSub, subscribe to a topic, send an event and then clean up. In total, its 82 lines of code including liberal line breaks. Even if you have never written or read a line of Go before, I hope you'll agree that it's quite clear and readable:
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Kafka alternatives
Pub/Sub
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Top 6 message queues for distributed architectures
Google Cloud Pub/Sub is a fully-managed, globally scalable and secure queue provided by Google Cloud for asynchronous processing messages. Cloud Pub/Sub has many of the same advantages and disadvantages as SQS due to also being cloud hosted. It has a free and paid tier.
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Job Scheduling on Google Cloud Platform
Cloud Pub/Sub: A global messaging service for event-driven architectures
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Messaging Patterns 101: A Comprehensive Guide for Software Developers
Google Cloud Pub/Sub (*https://cloud.google.com/pubsub*)
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Effortlessly Scale Your Applications with FaaS: Learn How Functions as a Service Can Help You Grow and Thrive
Google Cloud Functions is a FaaS offering from Google Cloud Platform (GCP). It allows developers to run their code in response to events, such as changes in a database or the arrival of a message in a Pub/Sub topic. Like AWS Lambda, Google Cloud Functions can be used to build a variety of applications, including serverless websites, data processing pipelines, and real-time data streams.
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Mixing GCloud and F#
that gets triggered when a Pub/Sub topic is fired (from the webhook function)
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What is the best data storage solution for high-frequency (near real-time) updates
Maybe Pub/Sub from GCP?
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Kafka on GKE cluster security guidelines
I'm curious - given your limited knowledge, is there a reason you're looking to self host this in your own cluster rather than using a managed service like https://cloud.google.com/find-a-partner/partner/confluent-inc?redirect= or just native Google PubSub https://cloud.google.com/pubsub/ ?
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Moving to Google Cloud managed services, from a FinOps point of view
Pub/Sub, the GCP managed service for message queuing, has two levels of services on standard and one Lite. Standard is the high availability version of it and Lite could be a zonal or regional service with infrastructure managed by the client. Obviously, the model pricing will be very different with a x10 between Standard and zonal Lite. However, the model pricing is the same is based on throughput for message publishing, message storage costs and egress for message distribution. Here, we totally break the similarity with a VM model (except on storage). Everything is drived on volumetry and performance of inbound and outbound messages.
What are some alternatives?
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
twitch - Interact with Twitch's API, chat and subscribe to events via PubSub and EventSub.
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
mitt - 🥊 Tiny 200 byte functional event emitter / pubsub.
dagster - An orchestration platform for the development, production, and observation of data assets.
svelte-persisted-store - A Svelte store that persists to localStorage
rudderstack-docs - Documentation repository for RudderStack - the Customer Data Platform for Developers.
RabbitMQ - Open source RabbitMQ: core server and tier 1 (built-in) plugins
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
NATS - High-Performance server for NATS.io, the cloud and edge native messaging system.
streamlit - Streamlit — A faster way to build and share data apps.
MySQL - MySQL Server, the world's most popular open source database, and MySQL Cluster, a real-time, open source transactional database.