Akamai Cloud Computing (formerly Linode) include scalable and accessible Linux cloud solutions and services. These products and services support developers and enterprises as they build, deploy, secure, and scale applications.
$5
per month
Google Cloud Datastore
Score 7.7 out of 10
N/A
Google Cloud Datastore is a NoSQL "schemaless" database as a service, supporting diverse data types. The database is managed; Google manages sharding and replication and prices according to storage and activity.
N/A
MongoDB
Score 8.9 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
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Akamai Cloud Computing
Google Cloud Datastore
MongoDB
Editions & Modules
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Shared
$0
per month
Serverless
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Dedicated
$57
per month
Offerings
Pricing Offerings
Akamai Cloud Computing
Google Cloud Datastore
MongoDB
Free Trial
Yes
No
Yes
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
Yes
No
No
Entry-level Setup Fee
Optional
No setup fee
No setup fee
Additional Details
CPU, transfer, storage, and RAM are bundled into one price. Storage capacity can be increased with additional Block Storage or S3-compatible Object Storage. Instant Backups can be added with complete independence to the stack. Linode NodeBalancers ensure applications are available.
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Fully managed, global cloud database on AWS, Azure, and GCP
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Akamai Cloud Computing
Google Cloud Datastore
MongoDB
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Amazon Web Services is vast and expansive, but far too expensive for what we need it to do. Azure is a more plug-in hosted solution, but again the price isn't worth it. I can use dokku to ape the functionality of heroku for far less than the latter charges. Digital Ocean's …
We selected Google Cloud Datastore as one of our candidates for our NoSQL data is because it is provided by Google Cloud, which fits our needs. Most of our infrastructure is on Google Cloud, so when we think about the NoSQL database, the first thing we thought about is Google …
In our early development days we weighed NoSQL databases like MongoDB with RDBMS solutions like MySQL. We were more familiar with MySQL from past experience but also were wary of painful data migrations that slowed down development iterations and increased the risk of outages …
It does not belong to certain cloud platforms. MongoDB is an independent program that works with any cloud platform including Amazon Web Services and the Google Cloud Platform. For companies who want to maintain a cloud agnostic structure, MongoDB is a great choice for NoSQL …
Akamai Connected Cloud Linode would be a good service to host a content delivery network (CDN) because of its edge network but I'd prefer not to use Akamai Connected Cloud Linode for tasks that need GPU power such as Machine Learning or Artificial Intelligence (AI) because Akamai Connected Cloud Linode lacks deep GPU compute compared to AWS or Google Cloud or Microsoft Azure
If you want a serverless NoSQL database, no matter it is for personal use, or for company use, Google Cloud Datastore should be on top of your list, especially if you are using Google Cloud as your primary cloud platform. It integrates with all services in the Google Cloud platform.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
I've been with them a long time. They provide me with the capabilities I need coupled with knowledgeable support that's not pay-for-extra. However, if I move to a non-Linux OS, the level of support by necessity will drop off. I can still ask questions about the infrastructure but I my ability to ask about OS features will decrease.
For the amount of use we're getting from Google Cloud Datastore, switching to any other platform would have more cost with little gain. Not having to manage and maintain Google Cloud Datastore for over 4 years has allowed our teams to work on other things. The price is so low that almost any other option for our needs would be far more expensive in time and money.
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
Simple and clear, no BS interface. From a design perspective it's no Apple or Stripe, but it does what it needs without making me want to stick a fork in my eyes, like when being forced to use Azure, AWS or GCP.
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
There is very little planned downtime. Whenever planned downtime is necessary I'm always given lots of advanced notice and an explanation that I can pass along to my users that they'll understand. I really appreciate that Linode appreciates my commitment to reliable service to my users. It shows that they believe they've been successful when I'm successful.
Servers are well dimensioned and price performant. Of course one always wants more, so if they were to upgrade their hardware for the same price I'd consider moving more workloads. Networking - never had an issue. Hardware speeds - disks are fast and can grow to great size.
Support was excellent and fast. The documentation is extensive and helpful. I learned many things from their online documentation. I did not contact them by phone, but email took a day or less. Complex problems would probably need a service contract. I liked the friendly and polite tone of the support.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
We got kick started with an initial walkthrough along with some free credits. The initial walkthrough helped us to understand Linode's ecosystem and start our hands on with Linode. We tried out some apps from Marketplace initially with the free credits, which not only helped us understand Linode better, but also those apps. We had implemented many such apps to our customers with Linode
We're a small organization. The implementation of our Linode solution was trivial. Once I justified a cloud server to my bosses over a co-location -- the co-lo wasn't as fast as our linode server in load tests -- it was a matter of moving one Linux implementation to another. Trivial.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
We switched to Linode from Namecheap due to poor uptime, and never had any issues with stability ever again after switching. We also cut our costs in half by switching. We compared Linode to DigitalOcean and Vultr, with the primary factor that caused us to go with Linode initially being their documentation. After using Linode for 3 years, their amazing support is another reason why we wouldn't consider anyone else at this point.
We selected Google Cloud Datastore as one of our candidates for our NoSQL data is because it is provided by Google Cloud, which fits our needs. Most of our infrastructure is on Google Cloud, so when we think about the NoSQL database, the first thing we thought about is Google Cloud Datastore. And it proves itself.
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
Although I use only a fraction of their product offerings, the total set makes scalability an easy goal to shoot for. As I said, I have a few customers that use the services my Linode provides...and I like it that way. However, should I need to scale up, I can...without incurring any more cost than I need to.
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
