Grapple's answer:
Grapple is built for small to medium-sized companies who haven't successfully implemented traditional BI software like Looker, Power BI, Tableau, or other solutions like DataRails and Domo. Traditional BI software requires a lot of technical knowledge to setup, maintain, and they often make it really difficult for less technical users to customize. This means your dashboards either 1) don't work, or 2) aren't flexible and easy to use enough to let operators adjust them as they need during the course of businesses.
Grapple is designed from the beginning for non-technical operators across marketing, sales, and finance.
Grapple's answer:
Grapple is great for data savvy operators who love working with data. We're particularly helpful for companies with 25 to 500 employees who serve other businesses (B2B) and are focused on improving their CRM analytics and SaaS metrics. If you're using apps like Salesforce, Hubspot, Zendesk, Stripe, or Asana, Grapple is for you!
If you want to write data notebooks in python or SQL and want under-the-hood control of your data stack, Grapple is not for you. We recommend you try Omni or Hex.
Grapple's answer:
Jack, co-founder/CEO, had the idea for Grapple a couple years ago after spending almost a decade building in Tableau, Looker, Google Data Studio, Trevor.io, and the list goes on! Jack spent a lot of time collaborating with non-technical users in sales, marketing, bizops, finance on dashboards and after one particularly simple report that was still difficult to generate, he thought there must be a better way! Turns out, most data platforms require a ton of other tools and a ton of other people all of which are slow and expensiveโdelaying your time-to-insight. Jack had the idea to compress the data stack into a single tool, that maybe couldn't do everything, but would be the fastest, easiest way to pull the types of reports he pulled all the time over the last 10 years. Fast-forward to today, Andrew joined as co-founder/CTO and Grapple is now generally available and includes a suite of AI features to take Grapple's speed and ease of use even further. Let us know what you think!
Grapple's answer:
Grapple is a fully vertically integrated data platform and does not require any additional tooling. Unlike competitors Looker and PowerBI, Grapple includes everything you need to get started. Frustrated by your slow data team? Get started with Grapple right away.
In nerd speak, Grapple seamlessly bundles the following tools, you won't even need to manage them: - An ETL and data warehouse for centralizing your data - Automatic data modeling so your data is queryable right away - Visualization and analytics UI
And on top of all that, Grapple provides modern functionality too: - Unlimited Viewers: share your dashboards with as many users as you want, just like a Google Docs - AI/Natural Language: customize your dashboard with natural language instead of SQL or spreadsheet formulas - Straightforward pricing: pay as you go with monthly per user pricing
Grapple's answer:
Grapple's application layer is written in React + Laravel and under the hood uses a mixture of PostgreSQL and No-SQL to deliver data warehousing and analytics capabilities.
Based on our record, Apache Flink seems to be more popular. It has been mentiond 45 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In the meantime, other query engine support is on the roadmap, including Apache Spark, Apache Flink, and others. - Source: dev.to / about 2 months ago
Many stream processing systems today still rely on local disks and RocksDB to manage state. This model has been around for a while and works fine in simple, single-tenant setups. Apache Flink, for example, uses RocksDB as its default state backend - state is kept on local disks, and periodic checkpoints are written to external storage for recovery. - Source: dev.to / 3 months ago
Because the hosted catalog is a standard JDBC catalog, tools like Spark, Trino, and Flink can still access your tables. For example:. - Source: dev.to / 3 months ago
I wrote a python based aircraft monitor which polls the adsb.fi feed for aircraft transponder messages, and publishes each location update as a new event into an Apache Kafka topic. I used Apache Flink โ and more specially Flink SQL, to transform and analyse my flight data. The TL;DR summary is I can write SQL for my real-time data processing queries โ and get the scalability, fault tolerance, and low latency... - Source: dev.to / 4 months ago
Continuous Learning: Leverage online tutorials from the official Flink website and attend webinars for deeper insights. - Source: dev.to / 5 months ago
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