Re: How to choose a database

Also cockroach DB showing up 100K transactions per seconds in the blog below.

Now my apology if the question is silly here, btw are they able to achieve these figures because they are operating on distributed shards so the point of contention is distributed? Also are they doing those transactions in batches to get those figures, because if someone inserts 500million rows using a batch size of ~1000, then that will be ~500K database calls/transactions but not ~500million calls/transactions. And it would be easier for databases to handle those 500K batched transactions easily as there will be less chatter as compared to 500million individual transactions or say row by row transactions as we say it and each of that would involve context switching/network round trips ,connection management,parse calls etc between application and database engine. Correct me if my understanding is wrong?

https://www.cockroachlabs.com/docs/stable/performance.html

On Wed, Apr 26, 2023 at 8:49 AM Pap <oracle.developer35_at_gmail.com> wrote:

> Thank you Mladen.
> I saw those figures from Oracle as somebody posted doing 1M transactions
> per sec achieved using shards. But also saw some blogs stating 20K TPS
> achieved using distributed database yugabyte DB. Are those not the true
> figures?
>
> https://www.yugabyte.com/blog/mindgate-scales-payment-infrastructure/
>
>
> https://blogs.oracle.com/database/post/oracle-bluekai-data-management-platform-scales-to-1-million-transactions-per-second-with-oracle-database-sharding-deployed-in-oracle-cloud-infrastructure
>
> And yes, It's an up and running system which is catering to the business.
> But the new system is completely written from scratch
> (mostly because the existing system complexity is increasing day by day)
> using modern techstacks microservices etc so as to cater future growth and
> provide required scalability, resiliency, availability etc.
>
> On Wed, Apr 26, 2023 at 2:14 AM Mladen Gogala <gogala.mladen_at_gmail.com>
> wrote:
>
>> On 4/25/23 15:07, Lok P wrote:
>>
>> " *For now, I am only aware that the database requirement was for a
>> financial services project which would be hosted on AWS cloud and one RDBMS
>> for storing and processing live users transaction data(retention upto
>> ~3months and can go ~80TB+ in size, ~500million transaction/day) and
>> another OLAP database for doing reporting/analytics on those and persisting
>> those for longer periods(many years, can go till petabytes).* "
>>
>> 500 million transactions per day? That is 5787 transactions per second.
>> Only Oracle and DB2 can do that reliably, day after day, with no
>> interruptions. You will also need very large machine, like HP SuperDome or
>> IBM LinuxOne. To quote a very famous movie, you'll need a bigger boat. I
>> have never heard on anything else in the PB range. You may want to contact
>> Luca Canali or Jeremiah Wilton who have both worked with monstrous servers.
>>
>> Not only will you need a bigger boat, you will also need a very capable
>> SAN device, preferably something like XTremIO or NetApp Flash Array. With
>> almost 6000 TPS, the average time for the entire transaction is 1/6 of a
>> millisecond. In other words, you need I/O time in microseconds. The usual
>> "log file sync" duration of 2 milliseconds will simply not do. You will
>> need log file sync lasting 200 microseconds or less. Those are the physical
>> prerequisites for such a configuration. You will also need to tune the
>> application well. One full table scan or slow range scan and you can kiss
>> 6000 TPS good bye.
>>
>> Your description is pretty extreme. 6000 TPS is a lot. That is an extreme
>> requirement which can only be achieved by the combination of specialized
>> hardware and highly skilled application architecting. Fortunately, there is
>> oracle-l, which can help with the timely quotes from Douglas Adams, Arthur
>> C. Clarke and Monty Python. And of course: all your base are belong to us.
>>
>> --
>> Mladen Gogala
>> Database Consultant
>> Tel: (347) 321-1217https://dbwhisperer.wordpress.com
>>
>>

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