simplest use https://www.quantopian.com/ or just get data from quandl.com and use the pandas library sql and a database ... thats a complicated mess
may the force be with you and you strike it rich with MultiCharts. If it works for you then all the more power to you. I would describe none of your mentioned platform worthy even a trial. But everyone has different needs...apparently...
Um, ever heard of easylanguage ? use multicharts the easylanguage edition with portofolio backtester. But anyway, it's just EOD data, with 2K stocks 10 years its just 5020000 data points. AND your using very simple indicators , RSI and SMA I'll just write something up in Java and GA for a possible optimum solution. Since it's mostly linear so there won't be any local maxima trap i think.
Have you had much experience with Quandl EOD stock data? How reliable is the service with regards to regularity of data updates, price/volume data quality and correctness of the symbol list?
Not to threadjack, but a quick question for @volpunter . We've spoken in the past about noSQL and SQL as it pertains to tickdata. I know SQL as a language isn't optimized for timeseries, but do you think some of the changes in SQL Server 2012 and 2014 will help SQL make up some ground there? I'm particularly talking about the column store index in 2012 (I believe that's when they added it) and in-memory tables and indexes in 2014. I'm not saying that SQL is *optimal*, but certainly theres a reason so many people want to use it (for me, it's because I'm just learning and there are a lot of resources there...I suspect that more generally the preference is just there because SQL is so ubiquitous). I suspect avoiding the multiple JOINs is really the key to speed here. Anyway, I've also been playing with using binary files for my tick data and I know that's something you've discussed. If you aren't familar with already, I found this pretty cool: http://teafiles.codeplex.com I've decided I'm probably gonna stick to the nice integration of VS C# and SQL server (microsoft really really spoils students with dreamspark) until I really get a system im happy with here and THEN I'm going to pay the database choice and optimization game afterwards, but the teafiles + LINQ in .NET appears to be a pretty good tool. If you receive a feed and want to persist that, this seems like it would provide pretty easy speed there as well.
Found some new buzz words on the internet? Adrian or whoever you are, I am not condescending I just do not have much patience with those who try to impress or otherwise talk about things they know little to nothing about. Your mere mentioning of Multicharts or Tradestation reveals that you are not in this for a career. Nobody in the professional space would ever touch the platforms you mentioned simply because they are not proficient and do not expose enough functionality. So here are my 3 questions for you that I promised to ask: 1) How does your platform reliably handle non-base currency generated p&l? Can you easily reconcile trading in assets that are denominated in different currencies? 2) Can your platform(s) easily handle different asset classes? Currency options, futures options, index options, ETFs, bonds, bond futures, commodity futures? 3) Does your platform enable you to analyze time series as detailed as tick based quoting and trade reporting? How performant is it? Can you visualize single ticks and look at micro market dynamics in a visual sense and/or statistical sense? I can assure you that non of the platforms you mentioned are capable of the 3 above. But please provide insight if I missed something or am not fully up to date. You might say that you do not engage in hft and hence do not care about tick based data. But you should be concerned with such as well because you are directly exposed to micro market dynamics at the time of entering and exiting positions. If you find this condescending then I do not know what else to say. Again, if your Multicharts approach works for you then great for you, it would not for me.
a) to answer your SQL question, no I do not believe it makes it a more appealing solution just because they added on features they call "columnar database schema optimization". Sure, I believe operating on time series will become faster and faster via SQL as time passes but so does all technology in general improve over time. I remain steadfast in saying that it makes no sense to use SQL to operate on time series data. And why so many use it? Because so many here come from non-quant/non-trading backgrounds and know SQL because they are developers or because thats the first thing they read when they did a bit of research. Honestly when you do a google search for "database" what springs to mind first? SQL relational databases or columnar databases. Logically a lot in this world is relational and hence columnar databases by definition are a subset and special class of how to look at data and how to structure data. b) I did look at tea files a while ago and did not like the concept because too much, it locks you down to a fixed proprietary structure. They keep the actual tea file core logic/schema open-source (as far as I know) but put on top proprietary utilization of such logic, for example tea file data visualization and such. I really like to stick to own core logic so that I can extend and improve it over time. Also, there is very little to no support and the community around it is almost non-existent. But hey, this concept is still million times better than any SQL approach.
Sql is totally suitable for time series and most other types of data. This is the reason why everyone uses it. It's slow only for the poorly skilled people.