New answers tagged

0

Apache Cassandra would be a good fit. It's a partitioned row store, where rows are organized into table using a partition key. It is common use case to store time series data, you could simply use ticker and a period as partition key. Cassandra is optimized for writes and it's easily scaled, but you need at least 3 servers for it to run.


0

Apache Cassandra would be a good fit for storing real-time intraday data. It's a partitioned row store, where rows are organized into table using a partition key. It you use a schema where you store data for one ticker per row with partitioning by day or month (it has a limit of 2B records in a row), the operations in your questions would be very performant....


0

I am wondering if anyone has used NoSQL ... to store and analyze data. Yes. Have a look at arctic on github. This is an open-source API built on top of MongoDB, that is in production use by one of the largest hedge funds in the world, for storing time-series data. I would imagine that NoSQL would be much faster. In the github wiki you'll find links ...


0

manahl/arctic: High performance datastore for time series and tick data seems a good alternative for time series and tick data. It is built upon mongodb.


0

In regards to the above answers, for tick data or time series , you could probably use a combination of redis (in memory data-store) & mongodb, or use Hbase with bus events.


0

You can check whether your university has an access to Reuters or Bloomberg or else databases. In case it doesn't have any try Yahoo



Top 50 recent answers are included