Google Cloud SQL is a database-as-a-service (DBaaS) with the capability and functionality of MySQL.
$0
per core hour
Redis Software
Score 9.1 out of 10
N/A
Redis is an open source in-memory data structure server and NoSQL database.
N/A
SAP HANA Cloud
Score 8.9 out of 10
N/A
SAP HANA is an application that uses in-memory database technology to process very large amounts of real-time data from relational databases, both SAP and non-SAP, in a very short time. The in-memory computing engine allows HANA to process data stored in RAM as opposed to reading it from a disk which means that the data can be accessed in real time by the applications using HANA. The product is sold both as an appliance and as a cloud-based software solution.
$0.95
per month Capacity Units
Pricing
Google Cloud SQL
Redis Software
SAP HANA Cloud
Editions & Modules
License - Express
$0
per core hour
License - Web
$0.01134
per core hour
Storage - for backups
$.08
per month per GB
HA Storage - for backups
$.08
per month per GB
Storage - HDD storage capacity
$.09
per month per GB
License - Standard
$0.13
per core hour
Storage - SSD storage capacity
$.17
per month per GB
HA Storage - HDD storage capacity
$.18
per month per GB
HA Storage - SSD storage capacity
$.34
per month per GB
License - Enterprise
$0.47
per core hour
Memory
$5.11
per month per GB
HA Memory
$10.22
per month per GB
vCPUs
$30.15
per month per vCPU
HA vCPUs
$60.30
per month per vCPU
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Google Cloud SQL
Redis Software
SAP HANA Cloud
Free Trial
Yes
Yes
Yes
Free/Freemium Version
No
Yes
No
Premium Consulting/Integration Services
No
Yes
No
Entry-level Setup Fee
No setup fee
Optional
Optional
Additional Details
Pricing varies with editions, engine, and settings, including how much storage, memory, and CPU you provision. Cloud SQL offers per-second billing.
Every time you don't need a document DB, you can't go wrong with Redis over MongoDB. Google Cloud Pub/Sub may have solved one use case, but we'd still have to deploy Redis instances for other use cases, and adding another tech stack would only add complexity to our …
Redis was initially in the list of competitors like Aerospike, Cassandra, MongoDB.The major point that outset all others is that it provides a number of read and writes to the database that no one can match. Another major factor is Redis really knows the basic components that …
The in-memory performance is the key factor that got HANA sold to us. They also have a huge enterprise user base with nice sized communities to share a good or bad experience.
The SAP is stacked solid and is moving in the right direction.
Does what it promises well, for instance, as a sidecar for the main enterprise data warehouse. However, I would not recommend using it as the main data warehouse, particularly due to the heavy business logic, as other dedicated tools are more suitable for ensuring scalable operations in terms of change management and multi-developer adjustments.
Redis has been a great investment for our organization as we needed a solution for high speed data caching. The ramp up and integration was quite easy. Redis handles automatic failover internally, so no crashes provides high availability. On the fly scaling scale to more/less cores and memory as and when needed.
I think if you have a large organization, it's probably the product and the marketplace to go to. We're a large management consulting firm operating in four to seven countries. And generally speaking, I think that's the size and the scope where it scales best. I can't speak to smaller companies, but I can't see smaller companies leveraging the benefits as much as a larger organization can.
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.
Real-time reporting and analytics on data: because of its in-memory architecture, it is perfect for businesses that need to make quick decisions based on current information.
Managing workload with complex data: it can handle a vast range of data types, including relational, documental, geospatial, graph, vector, and time series data.
Developing and deploying intelligent data applications: it provides various tools for such applications and can be used for machine learning and artificial intelligence to automate tasks, gain insights from data, and make predictions.
We had some difficulty scaling Redis without it becoming prohibitively expensive.
Redis has very simple search capabilities, which means its not suitable for all use cases.
Redis doesn't have good native support for storing data in object form and many libraries built over it return data as a string, meaning you need build your own serialization layer over it.
Requires higher processing power, otherwise it won't fly. How ever computing costs are lower. Incase you are migrating to cloud please do not select the highest config available in that series . Upgrading it later against a reserved instance can cost you dearly with a series change
Lack of clarity on licensing is one major challenge
Unless S/4 with additional features are enabled mere migration HANA DB is not a rewarding journey. Power is in S/4
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.
We would rate our likelihood of renewing at 9/10. SAP HANA Cloud has proven to be a highly reliable and scalable data platform that consistently delivers strong performance. Its seamless integration with our overall SAP landscape, combined with improved analytics and real-time data capabilities, makes it a core part of our long-term technology strategy.
As with other cloud tools, users must learn a new terminology to navigate the various tools and configurations, and understand Google Cloud's configuration structure to perform even the most basic operations. So the learning curve is quite steep, but after a few months, it gets easier to maintain.
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.
It is very useful solution which provides you speedier data processing, real-time analytics. It helps you manage diverse data types. It also offers you excellent disaster management. It has user friendly interface which helps you navigate system and transactions easily and perform task smoothly.
GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.
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.
However, I am not the right person to answer this as we have another department to handle support and contact the service provider for any support required. Although i will say that they are the quick respondent and knows how to handle querry of the customers and provide quick and better support.
Professional GIS people are some of the most risk-averse there are, and it's difficult to get them to move to HANA in one step. Start with small projects building to 80% use of HANA spatial over time.
Unlike other products, Google Cloud SQL has very flexible features that allow it to be selected for a free trial account so that the product can be analyzed and tested before purchasing it. Integration capabilities with most of the web services tools are easier regarding Google Cloud SQL with its nature and support.
We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about and whether it was for us. We tried a bunch, but I can only seem to remember Mongo and Couch. Mongo had big issues early on that drove us to Redis and we couldn't quite figure out how to deploy couch.
I have deep knowledge of other disk based DBMSs. They are venerable technology, but the attempts to extend them to current architectures belie the fact they are built on 40 year old technology. There are some good columnar in-memory databases but they lack the completeness of capability present in the HANA platform.
Improved integration with Google Cloud, we have set up some automations with Google Workspace, and we have noticed that the raw data sharing between them is very fast as compared to using some other managed database, not sure why.
Due to some downtime during maintenance, we had to set up a relatively small service which ingested the data while this went down and dumped it when it came back up. So this was a negative impact on our ROI, since now we had to remedy this downtime against the same profit margins
It was cheaper than the legacy aws service since we needed large database instances
Redis has helped us increase our throughput and server data to a growing amount of traffic while keeping our app fast. We couldn't have grown without the ability to easily cache data that Redis provides.
Redis has helped us decrease the load on our database. By being able to scale up and cache important data, we reduce the load on our database reducing costs and infra issues.
Running a Redis node on something like AWS can be costly, but it is often a requirement for scaling a company. If you need data quickly and your business is already a positive ROI, Redis is worth the investment.
