Google Cloud BigTable vs. Redis Software

Google Bigtable is ONLY suited for massive data sets which scale PetaBytes and TerraBytes. Anything under this can easily be done via dedicated VMs and open source tools. Google Bigtable is expensive and shall be used wisely. It should be utilised only where it is well suited else you would simply be wasting dollars and not utilizing its full benefits.

Incentivized

Perfect solution for caching needs. If you have a bottleneck due to frequent data access to your database, then Redis can really help you by diverting those traffic away from your database. Its key/value pair structure also makes data lookup very efficient, providing excellent performance.

Incentivized

• Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
• Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
• Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.

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• Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
• Reliable. With a proper multi-node configuration, it can handle failover instantly.
• Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
• Fast. We process tens of thousands of RPS and it doesn't skip a beat.

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• User interface's responsiveness: I understand so much is going on under the hood, but laggyness is acceptable if a workload is running or being processed. In case their is not workload being process, GUI should work blazing fast. I have faced this at times, and this becomes frustrating as well.
• Nothing other than this - BigTable is quite efficient platform and does exactly what it is built for.

Incentivized

• Redis is super fast but it comes with a cost. Whole dataset resides in RAM. So it can be costly as primary memory is more costly, then secondary ones.
• Persistence issues: To achieve it, Redis uses a memory dump to create a persistence snapshot, that's cool. But it requires some Linux Kernel tweaking to avoid performance degradation while the Redis server process is forking. This further causes latency.
• Master-slave structure side effect: Master-slave architecture comes with its own side effects. Please note that there will be only one master with multiple slaves for replication. All writing goes to the master, which creates more load on the master node. So, when the master goes down, the whole architecture does.

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We will definitely continue using Redis because: 1. It is free and open source. 2. We already use it in so many applications, it will be hard for us to let go. 3. There isn't another competitive product that we know of that gives a better performance. 4. We never had any major issues with Redis, so no point turning our backs.

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For big IT firms like us, data is very important and it only holds its value if it can make sense to us. Therefore, Bigtable's usability is priceless when it comes to decision making based on data.

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It is quite simple to set up for the purpose of managing user sessions in the backend. It can be easily integrated with other products or technologies, such as Spring in Java. If you need to actually display the data stored in Redis in your application this is a bit difficult to understand initially but is possible.

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Google provides premium support services for BigTable which is absolutely blazing fast similar to Bigtable's performance.

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The support team has always been excellent in handling our mostly questions, rarely problems. They are responsive, find the solution and get us moving forward again. I have never had to escalate a case with them. They have always solved our problems in a very timely manner. I highly commend the support team.

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Whitelisting of the AWS lambda functions.

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UI isn't that great compared to the other competitors. The management of our memcached cluster was becoming pretty complicated as the application grew in size. Redis is a much better option compared to memcached. Redis is bit unreliable compared to the alternative RabbitMQ especially when it needs to be integrated with Celery.

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• Positive return on investment.

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• Existing tools like Redisson that were built over Redis reduced dev time in solving challenging problems, which had a positive impact on ROI.
• We initially misused Redis for persistent storage which had a negative impact on ROI because we were paying a lot for inactive users.
• The increased performance we achieved using Redis in areas like locking helped us improve the performance of our system reducing the likelihood of system timeouts.

Incentivized