Google Cloud Datastore vs. Progress MarkLogic

I feel like Google Cloud Datastore is well suited when the data models are simple and the possible filtering and sorting operation are not complex. With more complex filtering, the amount of required indexes increase, and so does the costs.

Incentivized

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.

Incentivized

• It is hosted in GCP, our primary cloud provider.
• It integrates with all the services we use in GCP.

Incentivized

• Search was really advanced. Hard to set up and had limitations about semantical meanings between xml nodes, but provided very good search abilities.
• The organization of documents across collections and metadata was particularly useful.
• The REST abilities were very advanced and worked with XQuery well.

Incentivized

• Part of the Google Cloud Platform walled garden.
• Pay for read/writes to the datastore, in addition to storage.
• Not many libraries exist.

Incentivized

• 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.

Incentivized

I give Google Cloud a full score because it satisfies our needs so well. We host most of our infrastructure on Google Cloud and using Google Cloud Datastore helps us to solve our NoSQL storage problem. and Google Cloud Datastore is so scalable and elastic. It saves us lots of time to maintain and saves us money.

Incentivized

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.

Incentivized

The simple implementation, together with the Google Cloud dashboard that allows data inspection, editing and querying, makes Google Cloud Datastore a comprehensive choice when it comes to NoSQL databases.

Incentivized

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.

Incentivized

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.

Incentivized

If deploying an application in Google Cloud Platform, using Google Cloud Datastore is a no brainer because of the simplicity of setup. Other options would require more setup and configuration, and do not come with the same level of guaranteed uptime as Google Cloud Datastore. In our case, we've been using Google Cloud Datastore for 4 years without any issues and have never had to think about it.

Incentivized

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.

Incentivized

• It solves our NoSQL database problem.
• It it highly scalable and available to meets our needs.

Incentivized

• 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.

Incentivized