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Ask HN: What to use for real time reporting?

2 pointsby ninjamayoalmost 9 years ago
I have this problem and was wondering if anyone can help. I have a number of data feeds (CSV files, web APIs) that I would like to report on but can&#x27;t find anything open source or paid that can do the job. Basically I want to be able to attach any data feed to this system and build a simple report (select fields, couple of aggregations) which are then distributed to my team. The system could either be a desktop app or web based, don&#x27;t mind. Each member of my team would have different levels of access to this and the report would present the data in tabular formats, charts and pivots. I looked at Tableau and Qlikview but they are not ideal for real time reporting.<p>Any ideas if there is anything like that out there?

2 comments

lsiunsuexalmost 9 years ago
I wrote something along these lines at work to monitor servers and stuff.<p>A few cron jobs query Google Analytics, server cpu, ram and hd free space, a specific mysql table total row count, etc... every minute and curl the results to Firebase.com<p>A separate web app in AngularJS 1.x stays open on one of my monitors so I can monitor the results all day.<p>Firebase can take in data a number of ways (curl, php, js, etc...) and with it&#x27;s realtime push - keeps the web app side of it fresh and current without having to refresh the page every minute via some other means.<p>You could also access the firebase data via iOS &#x2F; Android code if you wanted to get fancy.<p>Works for us.
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brudgersalmost 9 years ago
I think there is some ambiguity of terminology around &#x27;real time&#x27;. By which I mean that aggregation implies a temporal window and batching data and processing the data as a batch whereas really &#x27;real time&#x27; implies right now and a single datum and stream processing. The historical concepts are OLAP [online analytic processing] and OLTP [online transaction processing], respectively. More recent thinking is that batch is a special case of stream (or vice versa depending on the task).<p>Architecturally, it is common to use pub&#x2F;sub. Basically to ingest all the input streams into a single log type data structure and allow services to make calls against an API.<p>Boiled down to the simplest thing that might work:<p>1. Write each event in the input streams as text to a log file [OLTP]<p>2. Grep [maybe using tail] to find the interesting bits. [OLAP]<p>Where I am going is that the way a specific business is likely to solve this class of problems tends toward integrating several tools rather than something off the shelf because of issues like data integrity [i.e. it&#x27;s bad for a bank to drop data on the floor, it&#x27;s ok for the comments section of a blog].<p>The second reason that integrating tools makes sense is that issues like data access restrictions are more robustly handled at the operating system and network levels [avoids duplicating a core OS functionality and specific security&#x2F;access configurations] I&#x27;d mention that maintaining data silos is often more habit than necessity and providing full access to the data or only ingesting data appropriate for full access probably simplifies the design.<p>Anyway, to me this looks more like software development than swiping a credit card if the set of features is non-negotiable...although, I suppose the consultant route might open up that possibility.<p>Good luck.