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.
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Progress MarkLogic
Score 9.0 out of 10
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MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities. The vendor states it is the most secure multi-model database, and it’s deployable in any environment. They state it is an ideal database to power a data hub.
$0.01
per MCU/per hour + 0.10 per GB/per month
Pricing
Google Cloud Datastore
Progress MarkLogic
Editions & Modules
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Low Priority Fixed
$0.01
per MCU/per hour + 0.10 per GB/per month
Standard Reserved
$0.07
per MCU/per hour + 0.10 per GB/per month
Standard On-Demand
$0.13
per MCU/per hour + 0.10 per GB/per month
Offerings
Pricing Offerings
Google Cloud Datastore
Progress MarkLogic
Free Trial
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Free/Freemium Version
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No
Premium Consulting/Integration Services
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No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Community Pulse
Google Cloud Datastore
Progress MarkLogic
Features
Google Cloud Datastore
Progress MarkLogic
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
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 you are storing META data then MarkLogic is super useful as it retrieves everything so fast, while storing the whole data shows performance issues some times. If you have legacy systems then migrating from it would really require sweat and blood, on the other hand if you are in systems like Node.js you can simply integrate two systems easily. If you don't know how in the end your your data schema will look like then it's better to make a prototype using MarkLogic.
MarkLogic still has a long way to go in fostering the developer community. Many developers are gravitating to the simple integrations and do not delve into the deeper capabilities. They have made tremendous strides in recent months and I am sure this will improve over time.
Many of the best features are left on the floor by enterprises who end up implementing MarkLogic as a data store. MarkLogic needs to help customers find ways to better leverage their investment and be more creative in how they use the product.
Licensing costs become a major hurdle for adoption. The pricing model has improved for basic implementations, but the costs seem very prohibitive for some verticals and for some of the most advanced features.
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.
MarkLogic is expensive but solid. While we use open source for almost everything else, the backend database is too critically important. At this point, re-tooling for a different back end would take too much time to be a viable option.
Very little about it can be done better or with greater ease. Even things that seem difficult aren't really that bad. There's multiple ways to accomplish any admin task. MarkLogic requires a fraction of administrative effort that you see with enterprise RDBMS like Oracle. MarkLogic is continually improving the tools to simplify cluster configuration and maintenance.
There's always room for improvement. Some problems get solved faster than others, of course. MarkLogic's direct support is very responsive and professional. If they can't help immediately, they always have good feedback and are eager to receive information and details to work to replicate the problem. They are quick to escalate major support issues and production show-stopping problems. In addition to MarkLogic's direct support, there are several employees who are very active among the community and many questions and common issues get quick attention from helpful responses to email and StackOverflow questions.
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 had Fast in place when Microsoft had bought it up and was going to change / deprecate it. One of the biggest advantages of MarkLogic for search actually had to do with the rest of the content pipeline - it allowed us to have it all in one technology. On the NoSQL side, we looked at MongoDB a couple years back. At that time, MarkLogic came in stronger on indexing, transaction reliability, and DR options. For us, that was worth using a commercial product.
MarkLogic reduced the amount of time that the DevOps team needed to dedicate to database updates, as the engineering team was mostly able to easily design and maintain database upgrades without requiring specialists such as database architects on the DevOps side. This capability flowed from the product's speed and the versatility of its XQuery language and libraries.
MarkLogic required significant education and buy-in time for the engineering team.
