I think the nuances of the offering are not entirely clear from the marketing website, so here's what I've interpreted.
The product itself seems to be a Node.js framework that glues together various modules, including popular ones such as Express, Mongoose, & Socket.io. How they monetize it is via consulting and hosting, which they offer a fixed price for "unlimited" bandwidth and storage (very unclear how they may throttle this). The pricing is also exceptionally poor, a fast HTTP implementation may respond to 250k requests per second vs a month, and 5 GB of storage for $50 a month...
They seem to not have any sort of release strategy and the readme states to clone their repository. It would require pulling from their repo to update it as a dependency. There are also absolutely no tests, so you don't know if the latest commit is working or contains some work in progress or not. The signup process seems to be needlessly difficult, one needs to manually craft an HTTP request to some endpoint with some payload.
The "AI to build exceptional apps" pitch is vague. I can think of some possible cases such as automatic indexing based on querying patterns, but this is just speculative. I wouldn't trust it unless I know what it does.
- Yes, it does bundle frameworks but more importantly, it bundles databases like Mongo, Elastic, Redis etc. The idea is we completely abstract databases away from you and give you an API which does everything. We handle the rest like data sync between these databases, managing databases, scaling, etc.
- We're on a "Pay as you go pricing". Let me know your thoughts on this.
- I completely agree, we dont have a release strategy and we need to work on it. You'll see GitHub releases every week within few weeks from now. Thank you for the feedback.
- One of the visions of the product is to learn how your app uses the service and how your app queries the db - and auto optimize data between databases, so you never have to think about storing your data in different types of databases ever again.
On the last point--I think trying to do this is one of the big reasons Parse failed. Auto optimizing DBs is an incredibly complex and delicate task.
My Parse app's write performance suffered because my biggest table (27m rows, 10 small columns, 15GB) ended up with 17 auto-created indexes, taking up an additional 15GB of space.
I personally wouldn't call Parse a "failure" and without going into details, this has absolutely nothing to do with why Parse shutdown.
That said the real challenge, that other such platforms might not have, was handling all the very different DB workloads for all the apps we were hosting.
I worked on some of the pieces of that auto indexer. In most cases, this is a feature that was both necessary for us and extremely useful for our customers who didn't know how to manage their own DB. What was arguably missing was a way to expose the indexing operations to the developers, although this would have brought it's share of other challenges for obvious reasons.
If we created 17 indexes on the same collection (in some cases, it was way! more), that's because there were query families issued that needed those 17 indexes. I can't say this is your case, but in almost all instances I've seen, this was a result of poorly designed DB schemas and query patterns. Of course, for developers who know what they're doing, it's hard to design properly when you're dealing with a blackbox.
Yes, amplification and DB size are an issue when over indexing but our auto indexer was under constant tweaking and wasn't creating indexes "just because".
On their website [1], they make it look like WhatsApp, Slack, and Instagram are all using their service, when in reality it's their own implementation of "similar" services.
While true, I think you're nit-picking. They've clearly put a ton of effort into the project (code, docs, website), why is there something fishy or malicious?
I like your integrity man. Even after you fixed it you own the error when other people question the original comment. Good on you. Ownership, transparency and integrity are key to a service of this magnitude.
FYI. I do more front-end work and I'm starting to contribute more to open source. Is your website on a repo? If so, may I contribute some PRs to it that'll improve your website? I'll make really small ones so it's easier to absorb. Let me know if that is doable.
Ps. I'll be checking your product out btw since I like your attitude on HN and I bet on people not products.
Thank you so much for your kind words. Yes, our website is on a repo here : https://github.com/cloudboost/home. PR's are a LOT appreciated. Please also feel free to write me anytime at nawaz [at] cloudboost [dot] io
CloudBoost looks amazing. I can tell they've put a ton of effort into the app, docs, and website.
This brings me to their problem... Pricing! Their pricing (https://www.cloudboost.io/pricing) makes little to zero sense. First it is priced too low, a sign of future problems ahead. Second, I think they've got the entire model wrong. They should charge for bundles of API calls and GB of storage. Pay for what you use like cloud providers.
An example of pricing I would implement might look like $10 per GB of storage and $0.15 every 1k of API calls.
Thus a smallish example application that uses 2 GB of storage and makes 500,000 API calls a month would pay $95 / month.
I'm Nawaz from CloudBoost. 100% agree. The idea was when you reach a $99 plan, we install CloudBoost on your own Cloud. But a pay as you go service makes a lot more sense. If you want to install the service on your own machine, you can always check out our enterprise / open source options.
Thank you for your feedback again. This helped a lot.
Algolia's pitch is "much better results than you'd get from the average open-source search tool", not "hosted ElasticSearch". How does CloudBoost stack up? What special sauce makes this an open-source Algolia and not an ElasticSearch wrapper?
I used Parse and Firebase for a mobile app project a few years ago and I always felt the combination was necessary. Firebase is great for real time data like chat streams while Parse did all of the unexciting user account stuff.
I think Deepstream does Realtime and CloudBoost does a lot more - like Search, ACL's, RealTime, BLOB, JSON, and a whole lot more. You can also check out : https://cloudboost.io/compare
Not sure if it is the HN "hug of death", but I found the Cloudboost.io site quite slow to load up here. For a service touting scalability and fast performance, a slow marketing site doesn't lend to the credibility. Lets hope it is a temporary thing that will be resolved. I am excited by the project.
Actually the site loads about 4.3 MB of compressed data over the network, or 6.5 MB uncompressed.
Edit: out of curiosity, I looked at the package.json of their open source project, there are 51 top-level dependencies. After installing, there's 140 MB of dependencies, or about 800k lines of JS.
We currently use MongoDB Search for search, but are planning to integrate ES in about a month from now to make your search much better and faster. Let me know if this helps.
Thank you for pointing this out. Yes, we're working on making our API's comparable with Algolia. We've implemented basic search now and are working on advanced search API's.
"Today, apps need many data stores - from database to search index, to cache and more. Our AI algorithm learns about your app and auto configures these for you so we don't have to which saves 50% or more of your time."
The product itself seems to be a Node.js framework that glues together various modules, including popular ones such as Express, Mongoose, & Socket.io. How they monetize it is via consulting and hosting, which they offer a fixed price for "unlimited" bandwidth and storage (very unclear how they may throttle this). The pricing is also exceptionally poor, a fast HTTP implementation may respond to 250k requests per second vs a month, and 5 GB of storage for $50 a month...
They seem to not have any sort of release strategy and the readme states to clone their repository. It would require pulling from their repo to update it as a dependency. There are also absolutely no tests, so you don't know if the latest commit is working or contains some work in progress or not. The signup process seems to be needlessly difficult, one needs to manually craft an HTTP request to some endpoint with some payload.
The "AI to build exceptional apps" pitch is vague. I can think of some possible cases such as automatic indexing based on querying patterns, but this is just speculative. I wouldn't trust it unless I know what it does.