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So, why crawl 5m URLs, when 50k is enough? With a few simply adjustments, you can avoid wasting resource and time on these (more on adjusting the crawl shortly). Generally websites are templated, and a sample crawl of page types from across various sections, will be enough to make informed decisions across the wider site. Do you need to crawl every URL, to get the data you need?Īdvanced SEOs know that often it’s just not required. This is the question we always recommend asking. Do You Really Need To Crawl The Whole Site? SSDs are so fast, they generally don’t have this problem and this is why ‘database storage’ can be used as the default for both small and large crawls.

If you’re working on the machine while crawling, it can also impact machine performance, so the crawl speed might require to be reduced to cope with the load. However, writing and reading speed of a hard drive does become the bottleneck in crawling – so both crawl speed, and the interface itself will be significantly slower.

While not recommended, if you have a fast hard disk drive (HDD), rather than a sold state disk (SSD), then this mode can still allow you to crawl more URLs.
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The ‘Crawls’ menu displays an overview of stored crawls, allows you to open them, rename, organise into project folders, duplicate, export, or delete in bulk.Īn additional benefit is that as the crawl is automatically stored, if you do have a problem, such as a Windows update, power-cut, or crash, the crawl should still be retrievable from the ‘crawls’ menu to be resumed.

The database crawl can be accessed and opened via the ‘File > Crawls’ top-level menu. The other main benefit is that re-opening the stored crawl is much quicker in database storage mode than loading in a. In database storage mode, crawls are also automatically stored, so there is no need to ‘save’ them manually. As an example, a machine with a 500gb SSD and 16gb of RAM, should allow you to crawl up to 10 million URLs approximately. The default crawl limit is 5 million URLs, but it isn’t a hard limit – the SEO Spider is capable of crawling more (with the right set-up). Database storage mode allows for more URLs to be crawled for a given memory setting, with close to RAM storage crawling speed for set-ups with a solid state drive (SSD). We recommend this as the default storage for users with an SSD, and for crawling at scale. As a very rough guide, a 64-bit machine with 8gb of RAM will generally allow you to crawl a couple of hundred thousand URLs.Īs well as being a better option for smaller websites, memory storage mode is also recommended for machines without an SSD, or where there isn’t much disk space. Users are able to crawl more than this with the right set-up, and depending on how memory intensive the website is that’s being crawled. However, as machines have less RAM than hard disk space, it means the SEO Spider is generally better suited for crawling websites under 500k URLs in memory storage mode. Memory storage mode allows for super fast and flexible crawling for virtually all set-ups. However, there are some key differences, and the ideal storage, will depend on the crawl scenario, and machine specifications. What Are The Differences Between Memory & Database Storage?įundamentally both storage modes can still provide virtually the same crawling experience, allowing for real-time reporting, filtering and adjusting of the crawl.
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The guide below provides a more comprehensive overview of the differences between memory and database storage, the ideal set-up for crawling large websites and how to crawl intelligently to avoid wasting both time and resource unnecessarily. 5 million URLs to be crawled.Īvoid over-allocating RAM, there is no need, it will simply slow down your machine performance. 2 million URLs, allocate 4gb of RAM only.
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If you’d rather not read the full guide below, below are the two main requirements to crawl very large websites.ġ) Use a machine with an internal SSD, and switch to database storage mode (‘Configuration > System > Storage Mode’).Ģ) Allocate RAM (‘Configuration > System > Memory Allocation’).
