High throughput and minimal latency for high-speed transactions
Handling millions of connections and billions of transactions every day is a challenge for current system architecture faced by many organizations. For financial organizations, with big data analytics requirements, the ability to process data in real-time and ensure high throughput and minimal latency can be critical.
Speed has different meanings depending on what we need. How fast can the system process and input? Usually translates to throughput. How fast does the user get a response from that input? usually translates to latency.
What are Throughput and Latency?
Let’s dig in a little deeper into throughput and latency to really understand the difference.
Latency is the amount of time it takes to complete an operation. This translates into how fast a user can get a response to his request.
Low latency means that the system responds quickly, mili-seconds, after an user sent out a request. Faster response time means more users and revenues, especially for high frequency trading companies. A mili-second delay in a trade can result in the loss of thousands of dollars.
Throughput is the rate at which the system can process inputs. It is the volume of work done by your database and the average response time in a unit of time. Allowing you to monitor how quickly your server is able to process incoming queries. Database throughput is one of the most important database performance metrics.
With Memurai you can achieve throughput of millions of operations/second with sub-millisecond latencies including high speed transactions, job and queue management, and real-time data ingestion, with the minimal amount of resources.
Handling high-speed data ingestion
Fast data ingest ensures simple and versatile data processing. The downside of data ingest is that it can be a complex challenge to implement.
Memurai is a fully compatible Redis solution for Windows that inherits the benefits from Redis: extremely light-weight, super-fast and easy-to-use.
Memurai for fast data inges offers different options of implementations, (diverse set of data structures: Lists, Sets, Sorted Sets, Pub/Sub and Hashes) each one with its pros and cons. Depending on your needs you can choose the one that fits best for your business.
For financial transactions, IoT and fraud detection fast data ingest with Lists it’s recommended. Data is not lost when the subscriber loses connection and It’s easy to implement. On the cons side, as the data is duplicated for each consumer, it could not be the ideal solution depending on the scenario. It also presents a tight coupling of producers and consumers.
For financial transactions, IoT transactions and metering; Sorted Sets allows time-series queries and is efficient for cases where one client has numerous consumers. On the other hand, it takes more space and the implementation is more complex.
For ecommerce workflows, gaming, collections of logs and job and queue management you could choose fast data ingest with Pub/Sub. It’s easy to implement and producers and consumers are decoupled. On the other hand requires many connections and it’s not resilient to connection loss.
As you can see, even though data ingest can be beneficial for your business, it is important to have a clear plan and business needs to be able to choose the best option for you.
High availability to maintain rapid data transmission speed.
Memurai sub-millisecond or even faster response times make it the perfect fit for businesses that need to handle huge amounts of data in the least amount of time. Thanks to the scalability you can instantly scale your database as much as needed with no downtime or interruption to the service.
Memurai is a stable and predictable solution that eradicates the manual process to get the system running again when having a failover. Get top performance with incomparable response times and expert support.