Sad to see. We were one of their early paying customers in 2009/2010 (we got a great deal). Performance was fantastic over very large datasets, but the bugs, storage requirements (very expensive SANs) and query limitations became big problems for us. We moved away after a year.

Just recently one of our team has been looking at them again (following a strong benchmark being posted at mysqlperformanceblog). So I went and checked out the forums and saw it was pretty much in a similar state to when I last used it four years ago.

Sad to see they couldn't make it work. The team was always really friendly and quick to help with issues - good luck in the future.

Dang....they just raised $7.5m in February? http://venturebeat.com/2014/02/10/calpont-renames-itself-inf...

Curious if they are returning money to VC's or just really burned through that much in 7 months...

I've been playing with Infobright community edition but also evaluated InfiniDB. I found InfiniDB was not compressing my data nearly at all whereas Infobright was utterly jamming it down - factors of over 300x for even small datasets of ~2m rows.

I don't know what the differences are to produce that, but when it comes to storing as much crap as I was looking at, I was willing to design around the limitations that Infobright CE has (ie: no insert/update queries) rathre than deal with the massive extra disk cost. I have currently got 223m rows sitting in Infobright and it's taking about 38MB.

I really hope that the OSS project takes off and that InfiniDB sees some better compression implemented, similar to Infobright. The extra features that InifiniDB has over Infobright CE (not only insert/update but also a multi-threaded infile loader, for example) would convert me if only the compression were better.

I'm all new to this though so if there's some good reason why they differ so greatly I'm all ears and would love to know. Maybe I screwed something up in the configuration? I'm not sure.

Either way, it's sad to see them go. Columnstore databases fill a really useful application that I can only see growing over time as more and more operational data is collected by industry.

InfiniDB is/was a great idea. The unfortunate bit was just what a Rube Goldberg machine of a data store it was. I spent a good few days just getting everything provisioned from our automation.

It looks most of the successful MPP analytic databases are based on PostgreSQL (e.g. Greenplum, Redshift). It's sad to see that InfiniDB could not make MySQL work for them reliably.

Clear up a few things here for all the speculation. I was an architect at InfiniDB that came on in Nov 2013 to build out the Enterprise Manager which was coming to alleviate many of the provisioning, management and monitoring woes that customers were experiencing and help modernize those aspects. The first beta offering of which was early July, unfortunately the ship had sailed so to speak. So I know first hand how and why things did not work here. As with all things, take your lessons learned, move on. Success is not the path of learning, failure is (see survivorship bias)

Some notes: Labeling InfiniDB as MySQL+ is a gross underestimation of what it does. MySQL is used as the front end query parser, and that is about it. Everything else behind it was custom written, and that is where the power is.

As with all DB technologies, your use case is the primary thing that determines your mileage. Comparing InfiniDB to MongoDB is one of the first signs to me that you don't fully comprehend the differences between database architectures. For the use cases that InfiniDB was made for, we routinely were faster performing on a smaller footprint. Using InfiniDB as a document store can be done, but that is not what it was made for.

What people call 'big datasets' is relative. Some think 500GB is alot, some think 5TB alot. Coming from telecommunications monitoring background, I will appreciate your dataset when we are talking TBs a day of churn per monitoring point with hundreds and thousands of monitoring points. The size of dataset you are working with, along with your use case for analysis is the two most important things in determining the technology stack. InfiniDB operated at these higher end scales very efficiently. There is a reason why Impala was a primary comparison, and we would usually operate on fraction of the hardware they needed.

Best technology does not always win. See InfiniDB.

Decisions made by previous executive teams years in the past can set a course that cannot be corrected sometimes (not efficiently or without alot of money)

Patents are worth their weight in gold.

Being open source is great for the community, but is a challenge to a business to build consistent revenue. There were many big projects running InfiniDB with the open source version, but not contributing to revenue. Even if they did sign up with support, you need custom feature development and other big ticket items to make impact. Or you have to build a large customer base paying for support, and that takes time. With the multiple iterations of adapting the technology to different architectures over the years, that was hard to retain those customers consistently. Also many customers will pay for support for their rollout or initial deployment, but when the project is done, they feel they are adequate enough to live with open source only.

Just because a company raised $X in a month, does not mean all that money is slated for going forward from that month. On top of that, payroll is not cheap, and you would be surprised how quickly you can burn through money keeping the lights on. For those of you who think people at startups are working for pennies on the dollars, I would advise you it is not the case. And if you are one of those people, I wish you the best, and odds are there are other reasons why you are doing so. Why would good engineers work at discount? Equity? There is not enough of the pie to go around to make that sustainable. Most startups pay competitive market salaries.

InfiniDB was at a junction where it was time to go for it, or go home, and that is exactly what happened in 2014. The marketplace for data solutions with Hadoop rising, other MPP vendors consolidating, and bigger players entering the field, made it very competitive, and the time to swing for the fence was now, versus treading water and hoping.

Even with stars aligned and everything else, all you have done in a company is weight the opportunity of it succeeding, not guaranteed.

I really enjoyed my time with InfiniDB and the team there. I really do feel its a missed opportunity with some decisions that could have been changed several years ago. Not securing patents and probably choosing MySQL as a frontend are some of those.

Side note, core group of us at InfiniDB have landed at Tune, a company that has appreciated the technology of InfiniDB and what it can offer for their solutions. Look forward to this new opportunity and what we can provide to the ad and mobile analytics space.

Sad, wish they made it.

finally infinidb was terrible snyways... waste of space on the internet... die.