New answers tagged nosql
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You may want to take a look at Altibase products. ALTIBASE HDB is a hybrid (in-memory + on-disk) DBMS and ALTIBASE XDB which is a pure in-memory DBMS. They are both full ANSI and ACID compliant databases, and they both deliver transaction speeds well over 100K TPS. XDB's performance can reach to an extreme number at 1.5 million TPS when client app is ...
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You should check out VoltDB. It can handle extremely high transaction rates (>100K txns/sec/server) with read or write-heavy workloads, full ACID-compliance, including full synchronous (immediate) durability and multi-statement transactions (e.g. check if seat is still available, then assign ticket in the same transaction).
Full disclosure: I work for ...
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While 100,000 transactions per minute sounds like a lot, it's generally classed as a "moderate" transaction rate (100,000 tx/min / 60 sec/min = 1,666.7 tx/sec).
There are systems out there running typical RDBMS systems (not in-memory) that can handle well over 10x that transaction rate (sustained) on a single box. Granted, these are well-tuned systems at ...
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As per me, you must store your unstructured data in a NoSQL database.
MongoDB is a good choice to start with.
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I'll answer your question in an orthodox manner, with a twist of heresy:
Orthodoxy: You shouldn't store data in a column in a relational database that isn't "atomic."
Heresy: In your specific situation, you could -- maybe -- consider this blob of JSON to be an atomic object.
Years ago, Chris Date said it like this:
"A relation is said to be in first ...
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Your list of characters that must be supported clearly indicates you need nothing more than plain ascii.
If you want to stored this as text, then this ascii is your most compact way. But here are a few clarifications:
VARCHAR(10) does not "need" 80 bits. It may need 80 bits, if all characters are used, under ascii character set. If you only store 3 ...
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Once you go beyond the limitations you mention (until $out is supported at least), then your best option is Map Reduce. If you are going to run multiple Map Reduce jobs, I would recommend version 2.4 at least (uses V8 engine, muti-threaded). For an example of how to do a unique count with Map Reduce, take a look here:
...
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"Is this realistic to do with something like MongoDB?"
If "realistic" means can be engineered to produce acceptable performance then the answer depends on whether you will do with appropriate benchmarking before putting it into production. You can replace "MongoDB" in your question with anything from Access to Oracle and the answer remains basically the ...
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