Lytho Workflow vs. MongoDB

It's a flexible program that can be molded to fit most businesses. It's geared towards agencies but we've been able to use it successfully as an in-house solution. It's pretty intuitive for the most part and is easy for new hires or clients to get up and running pretty quickly.

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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.

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• Requests - Request forms are set up so that certain fields are required and there's a minimum turnaround time. This prevents others from submitting an incomplete request or requesting things last minute.
• Proofing - Chasing after people to approve a proof is always a pain, but the simplicity of Lytho Workflow makes it less of a pain. I can quickly remind people in the route to review the proof by clicking a button.
• Templates - I use templates so that a list of tasks is created for me when I accept a job. It also creates a timeline for when each task needs to be done.

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• 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.

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• Not being able to permanently delete inactive/old users (i.e. employees that are no longer with the company).
• Search filtering features are lacking.
• Not being notified when someone replies to my comment without @ mentioning me.

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• 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.

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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.

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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.

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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.

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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.

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The corporate communication team uses DivvyHQ, TweetDeck and Agorapulse. Each one is used for different purposes and helps us meets our objectives. DivvyHQ helps Unum and Colonial Life's corporate communications teams stay in touch with one another's work and aware of what the other is doing. It allows for content collaboration and keeps us on track to meet individual deadlines.

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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.

• This has saved man power by automating certain functions
• We have created a new stream of marketing.

• 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