Solid state drives (SSDs) have become increasingly popular in recent years as an alternative to traditional hard disk drives (HDDs) for many computing applications. SSDs offer a number of potential advantages over HDDs, including much faster read/write speeds, better reliability, and lower power consumption. These characteristics make SSDs an appealing option for hosting databases, which require fast data access and high input/output (I/O) performance. However, SSDs also have some limitations that need to be considered when using them for databases. In this article, we will examine the pros and cons of using SSDs for database storage and help you decide if SSDs are the right choice for your database needs.
Advantages of SSDs for Databases
Here are some of the main benefits of using SSDs for database storage:
Faster Read/Write Performance
One of the biggest advantages of SSDs over HDDs is the faster input/output operations per second (IOPS) that SSDs can sustain. While a typical hard drive can manage 100-200 IOPS, modern SSDs can handle tens of thousands of IOPS with very low latency. This makes a huge difference for database performance, as databases need to constantly read and write data to storage during queries and transactions. The faster the storage, the faster those operations can complete.
With SSDs, databases can achieve significantly lower query response times and higher overall throughput. For latency-sensitive applications or databases with heavy transactional workloads, this speed advantage of SSDs can provide huge performance improvements.
Since SSDs have no moving parts unlike the mechanical HDD, they are more resistant to physical shock, operate silently, and have lower failure rates. Databases store critical business data, so uptime and reliability are paramount. The higher reliability of SSDs versus HDDs can result in less downtime for database servers.
SSDs are not foolproof, but on average SSDs have a much longer lifespan than HDDs. Consumer grade SSDs are rated for thousands of drive writes before failure, while HDDs typically last only a few years even in ideal conditions. Enterprise-grade SSDs can last even longer with specialized controllers and higher quality NAND flash memory chips. So if reliability is a top concern, SSDs are a wise choice.
SSDs come in a much more compact footprint than HDDs. A typical 2.5″ SSD can store up to 4TB, while a 3.5″ HDD would need to be 12TB or larger to match that capacity. This smaller and lighter physical design allows SSDs to be used in smaller servers, blade servers, and high density server farms. For databases where physical space or weight are a constraint, SSDs make storage more manageable.
The compact design also allows SSDs to be packed closer together in storage arrays. This can increase the storage density substantially compared to HDD arrays, making better use of limited space in data centers. High density SSD arrays provide incredible storage capacity for databases to scale and grow.
Lower Power Consumption
Since SSDs only use power when reading or writing data, they consume much less idle power than spinning hard drives. The mechanical components of HDDs require substantial power usage even when not in active use. For large database servers that may house hundreds of drives, the power savings from SSDs can be significant.
Not only do lower power needs reduce energy costs, it also lowers heat output. This reduces cooling demands in the data center, further improving efficiency. Every watt saved on storage can instead be used to improve database server performance. So SSDs give more “bang for your buck” from the available power budget.
Faster Boot and Reboot Times
When rebooting database servers, the boot process is much faster with SSDs since they don’t have to wait for HDD spin up. Servers can complete the reboot and be back online serving database requests sooner. For mission critical databases with high uptime requirements, this improves availability.
Additionally, when initially launching a new database instance or expanding with more storage, SSDs allow allocation and formatting of storage pools to complete much quicker. This agility can be key for rapidly provisioning new resources to support evolving database workloads.
Disadvantages of SSDs for Databases
While SSDs have some clear benefits, there are also some downsides to evaluate:
Higher Cost Per Gigabyte
SSDs currently cost substantially more per gigabyte of storage compared to HDDs. While SSD prices have come down dramatically over the years, HDDs remain significantly cheaper upfront for large storage volumes. The premium price of SSDs can make outfitting high capacity databases prohibitively expensive.
However, considering the performance, reliability, and operational benefits of SSDs, many find the higher initial investment justifiable. The data stored in databases is often so critical that the ROI from improved uptime and throughput outweighs the higher procurement costs. But the higher price per gigabyte is still a deterrent for some use cases.
Wear Leveling and Lifespan Considerations
While today’s SSDs are highly durable, they do have a limited lifespan and their performance declines over time. This is due to the inherent nature of NAND flash memory which wears out after a number of write cycles. SSD controllers use a technique called wear leveling to distribute writes across all the memory chips and optimize lifespan.
But at a certain point performance will drop and eventual failure is inevitable. Workload patterns that involve very heavy writing will cause faster degradation. For databases that need consistent performance over many years, wear leveling needs careful consideration.
However, modern SSDs generally last long enough to outlive other server components. And enterprise SSDs with extra over-provisioning space and smarter wear leveling algorithms have very long usable lifespans. For most database workloads, wear leveling is manageable if using business-class SSDs. Consumer SSDs are not recommended for databases.
Risk of Data Loss During Power Failure
NAND flash memory in SSDs uses voltage to maintain the state of stored bits. When power is lost, this state can be lost if the data wasn’t already committed to permanent storage through the SSD’s caching mechanisms. HDDs retain their magnetic state without power.
This is only a concern in disaster scenarios like sudden power outages. Production database servers use battery backups, RAID mirroring, and data commit logging to avoid potential data loss. However, the power requirements are a difference to consider between HDDs and SSDs. Proper handling of caching and battery backups is necessary with SSDs.
Not Ideal for Archival Data
If you have archival database data that rarely gets accessed, HDDs might make more economic sense than SSDs. The lower per-gigabyte price of dense HDD storage can offset the downsides of slower access for inactive data. SSDs are best suited for databases with active working datasets where performance matters most.
For long term archival, tape drives are actually optimal from a cost perspective. So SSDs are preferable for active databases, while archive data can go on HDDs or tape storage if performance is less critical. This tiered strategy provides the right storage medium for different database workloads.
Use Cases Where SSDs Shine
Here are some examples of database workloads and use cases where SSDs can make the most impact:
Online transaction processing (OLTP) databases that service high volumes of transactions from user applications require very fast I/O. The sub-millisecond latencies of SSDs can allow 2-3X as many transactions per second compared to HDD-based systems. Financial trading systems, e-commerce websites, and real-time analytics are examples that benefit greatly from SSD transactional performance.
Caching and Temporary Tables
Many databases use SSDs for caching frequently accessed data in memory or for temporary tables/files during query processing. Having this high speed storage tier on SSDs avoids slower disk access for caching and intermediary data. The faster operations can substantially speed up total query runtime.
Small Database Servers
For small database servers that don’t need massive amounts of storage, outfitting the entire system with SSDs makes sense. The servers benefit from fast boots/restarts, compact size, and low power needs. Smaller databases are less cost prohibitive for full SSD storage.
High Performance Parallel Processing
Large database analytics clusters that use parallel processing optimize job completion times by using as many CPU cores as possible. But storage performance needs to keep up with all that processing power or else it becomes the bottleneck. SSD scale-out storage architectures supply the IOPS necessary for high performance parallel database workloads.
Low Latency Requirements
For databases supporting applications where consistent low latency is critical, like real-time trading systems, SSDs provide the response times needed. Variability in latency is also reduced with SSDs, allowing more predictable performance.
SSD vs. HDD Cost Comparison
While SSD costs are dropping over time, a cost comparison shows HDDs are still substantially cheaper per gigabyte in most cases:
|Storage Type||Cost Per GB|
|Hard Disk Drive (HDD)||$0.03 – $0.05|
|Solid State Drive (SSD) SATA||$0.10 – $0.30|
|SSD SAS||$0.20 – $0.60|
|SSD NVMe||$0.20 – $0.50|
So HDDs are around 3-10X cheaper in terms of capital expenditure per gigabyte. However, over time power, cooling, and reliability costs add up substantially for HDDs. And performance benefits like supporting more database transactions per server can outweigh hardware costs. The break-even analysis depends on the specific use case and workload requirements.
Maximizing Endurance of SSDs
Since SSDs do have a finite endurance before performance declines, it helps to optimize database workloads and storage configuration to extend SSD lifespan if possible. Here are some best practices:
– Use enterprise SSDs designed for write-intensive workloads (with better wear leveling algorithms, higher quality NAND, more over-provisioning). Consumer SSDs won’t last.
– Size the SSD capacity significantly above the database storage footprint to allow liberal over-provisioning space for wear leveling. At least 25% over-provisioning is recommended but higher is better.
– Separate log files and temporary tables/files to a separate HDD volume to avoid excessive writes to the SSD. Those usages degrade SSDs quicker.
– Read-only data like reference tables should also go on HDD volumes instead of SSDs. No need to waste SSD endurance on read-only data.
– Use storage arrays with efficient SSD wear leveling algorithms and enterprise SSDs known for high endurance.
– Monitor SSD health metrics so aging drives can be replaced proactively.
SSD vs. HDD: Which is Better for Databases?
So which is better for your database, SSDs or HDDs? Here are some guidelines:
– For OLTP databases with heavy transactions, go all SSD for maximum performance. This optimizes critical transactions.
– For data warehouses doing heavy analytics, use SSDs for caching, temporary files, and most active data. Use dense HDDs for colder data.
– For small or midsize databases, SSDs complete tasks quicker and with lower latency. The premium versus HDDs is justifiable.
– For archival databases with infrequent access, HDDs still provide the lowest cost per terabyte. Use tiered storage with SSDs for active subsets.
– For mission critical databases demanding high reliability and uptime, SSDs are worth the investment.
– For cost sensitive databases with light workloads, HDDs might still be the best value. Not all applications require SSD performance.
So in summary, for most production databases, a combination of SSDs and HDDs in tiered storage configurations provides the best overall performance, capacity, and TCO. Pure SSD-based systems deliver blazing speed for transactional or latency-sensitive databases, but HDDs serve well for colder datasets. Weigh your performance needs, capacity requirements, and budget to design an optimal storage infrastructure.
SSDs provide major performance benefits for databases via much faster read and write speeds compared to traditional hard drives. This enables applications built on top of databases to become faster and more responsive. However, the higher cost per gigabyte of SSDs along with finite wearable lifespan need consideration.
For databases requiring high throughput and low latency like heavily transactional systems, SSDs are certainly warranted despite their downsides. But large archival databases may still favor high density HDDs for colder datasets. Most real world deployments find a combination of SSDs for hot data and HDDs for cold data offers the best blend of performance and storage capacity.
So while SSDs have limitations, their strengths like faster queries and higher reliability mean they are worth the investment for most production database workloads at enterprise scale. Carefully evaluating the needs of applications and databases allows designing a storage architecture that balances SSDs and HDDs to maximize benefits and minimize costs.