How to Speed Up System Data Acquisition Speeds


Whether you’re a provider or a user, getting access to the data you need as fast as possible is paramount. That is why you need your system to meet this demand by optimizing or upgrading it for the most streamlined experience. You can achieve this by making software changes or using better hardware.

To guide you on how you can go about this, we’ve made a list of the most significant changes to your system that you might have to make.

Improve your system’s cache

The cache is a part of your CPU that can hold smaller amounts of memory like data that you or your users use most. The cache is nearer to the CPU than RAM because these two share the same chip, making data stored there travel to the processor quicker.
Having the cache work as the middleman between the main memory and the processor reduces slow data retrieval speeds. This means the more cache memory there is, the faster your systems will run. You can improve your cache capabilities by using Gigaspace’s in-memory cache solution called InsightEdge Smart Cache which works on all operational data sources.

Lower your network’s latency

To speed up your system’s data acquisition processes, you’ll also need a fast internet connection, and you must undertake this with a two-pronged approach. The first is to acquire data from long distances or external sources, and for this, you will need a fast-paced ISP. Try to go for an ISP that offers a fiber connection as its latency is usually around 10-15 ms, making it faster than cable, DSL, and satellite.

Another change you can consider in internal data acquisition is using ethernet cables instead of wifi. Ethernet cables, especially CAT6 cables, are generally faster than Wi-Fi connections and all ethernet cables are more reliable, unlike wireless networks. With fiber and ethernet connections, your data systems will function well even if they’re used for working on blockchain projects.

Improve database queries

Inefficient SQL queries are the usual culprits when it comes to slowed data retrieval. Fixing these queries can help you prevent future performance issues and streamline your database’s performance. While doing this manually can sound tiring, the good news is that there are many SQL optimization tools that you can use.

A huge benefit that these tools offer is that they can analyze multiple query execution plans and show you the most efficient one. Many even enable automatic query rewriting, so you don’t have to manually search for queries or type the necessary changes.

Defrag your data

Fragmented files are another factor that you must look into when optimizing your data retrieval speeds. That’s because when files enter your disk, they may be broken up to fit on it; other factors like files being written, resized, and deleted will exacerbate it.

When these fragments are spread out, trying to access a file will take longer as these fragments will have to be read or written separately. Fortunately, many systems come with built-in defragmentation tools that you can use routinely. You can also utilize tools that prevent files from fragmenting after they’ve been defragged.

Optimize database indexes

Using indexes in your databases can improve data access speeds if you have to draw a file from a large data pool. What makes indexes obtain data faster is that you can set certain parameters for a search to make it shorter instead of going through each entry.

To optimally use indexes, you also have to know when you don’t need to use them. That’s because even though they shorten searches, they also use extra memory. You can achieve the best results when indexing by using as many indexes as you can without causing unnecessary memory allocation.

Optimize the CPU

Before upgrading your CPU, you need to compare your system’s actual requirements against both your current CPU and the one you want to upgrade to. That is because you may not need an upgrade. Sometimes making a few changes like reducing unnecessary processing power usage or allowing maximum CPU power usage can improve speeds.

If optimizing your current CPU doesn’t yield the results you hoped for, you need to buy a faster CPU compatible with your setup. For a CPU to be considered compatible with your setup, it must match your chipset and fit into your motherboard’s socket.

Take advantage of your system’s RAM capabilities

To fully realize your system’s RAM ability so data can get accessed faster, the first thing you must do is ensure the software is always upgraded to the latest version. That’s because older versions usually use more memory, and depending on the size of the programs you use, these can slow your system severely.

An alternative approach to fully utilizing your system’s RAM is by upgrading the chip, as most manufacturers will install one with less memory to save money. However, installing more RAM could also expand your system’s limitations, especially if it’s an older model.

Optimize disk space

When it comes to your database’s servers, storage is currency because it’s important for indexes and system performance improvements that normally use more space than they require. That’s why running databases on separate hard drives is important. Running databases on separate hard drives also reduces the chances of disk fragmentation happening.

When optimizing your disk space, you also need to look at the disks your system is using, as some disks may not be fast enough for your needs. To ensure that you get the most suitable disks, look for SSDs built for databases and then get one with enough space for your storage needs.

In conclusion

As we’ve listed above, the best way to achieve fast data acquisition speeds is to establish a balance between your system’s capabilities and what is required from it. Finding this sweet spot can save you both processing and monetary resources by ensuring that all optimization protocols are followed before an upgrade is deemed necessary. We curated these points with systems of varying slowness and demand in mind. That’s why we’re sure that you will benefit from these regardless of your organization’s size.

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