I have to start an application where I need to decide which db should I use
For complex queries which should I prefer mongodb or firestore
Thanks
Personally, I would choose MongoDB but that strongly depends upon which application you want to build.
MongoDB is open source and not Cloud based, it is high portable and supports many programming languages and external products, although query syntax looks a bit more complicated.
If you need auto scaling feature and integration with other Google services then Firestore would be the best choice.
To wrap up, MongoDB seems to be more secure and consistent while Firestore is better suited for mobile apps or application based on real time data.
Related
I have a string for eg: "My name is John" stored in Firebase.
How would I query firebase so I can find all the posts in Firebase that have "John" ?
I can search for the first term in a string now using:
DataService.dataService.BASE_REF.child("Posts").child(selectedComment.commentKey).queryOrderedByChild("userComment").queryStartingAtValue(comment).queryEndingAtValue(comment+"\u{F8FF}").observeSingleEventOfType(.Value, withBlock: { (snapshot) in
where comment = "My"
I read about using Elastic search with Firebase but wanted to check if there was an easier way in Firebase before I looked at ElasticSearch/Flashlight for Firebase,
Unfortunately, Firebase doesn't support searching thru content like that (in any language SDK). From a Google Groups Post in July '16:
As a company that understands search, we're also a company that
understands using the best tool for the job. For fuzzy matching and
contains, a NoSQL, realtime data store isn't the correct tool--these
queries would be slow and scale poorly. BigQuery or ElasticSearch are
the right tool for providing useful results in a scalable and robust
manner.
Right now, this involves deploying a small node script to sync your
search results with the realtime data, as explained in the article
with the sample Flashlight lib. In the future, it will become more
"effortless" as we add integrations between Firebase and Cloud
products, particularly Cloud Functions and BigQuery interoperability.
BigQuery is, as I understand it, not specifically designed for user-facing search.
Elasticsearch (specifically, the Firebase plugin Flashlight) is a potential solution, but as you alluded to, it's an incredible amount of overhead (deploying/managing or renting an ES cluster, configuring the plugin, etc.). If content search is an important enough part of your app to justify that time/$, you may want to consider solutions beyond Firebase for your database needs, as it's by far one of the service's weakest areas.
In my opinion, you have a few options beyond Flashlight:
Algolia, a Search-as-a-service provider, does offer integration with Firebase, but I've never used it & so can't offer much more than to say that it exists.
Another alternative might be maintaining a collection of documents you want to search on another service, like AWS Cloud Search
Depending on the stage of your project & your needs, consider other Backends-as-a-Service that support more in terms of querying. E.g., GraphQL-as-a-service backends, like Scaphold.io, Graph.cool, and Reindex are all built on SQL databases, and (I believe) all support multiple types of querying.
e-commerce is a product of microsoft.As i gone through the product i came to know that it is mandatory to use SQL server along with e-commerce sever.i want to increase the speed of the retrival process and want to use a NoSQL database like MongoDB in place of SQL.Is that possible? please advice.
No, you can't.
MongoDB can not be used as a drop-in replacement for SQL databases. It already starts with the different and incompatible query language.
But it goes on with them having a completely different way of handling data, which makes it superior in some roles, but inferior in others. Even when you would use some translation-middleware which mimics a SQL server and translates the query commands into the equivalents of the MongoDB database behind it and translates the response back, the performance would likely be a lot worse than with a native MSSQL database, because you would be using MongoDB in a way it wasn't meant to be used.
When you want to use MongoDB successfully, you completely need to change the way you model your data and the way you deal with it. This affects your whole application design. When you try to use MongoDB as if it were a relational database, you will be extremely disappointed.
The same applies to other NoSQL databases.
Also, not every problem is a good fit for every database technology. When it comes to eCommerce applications, you should really think twice before choosing a database technology which doesn't fully guarantee ACID in all situations. Most (not all!) SQL databases do, most (not all!) NoSQL databases don't.
My company has been used Oracle for a long time but we would like to look for a NoSQL database as a replacement for faster querying and flexible schema design.
I have tried to use MongoDB which would be the most popular NoSQL database nowadays. I connected it to Spring Data to do some simple queries, which is quite easy to be set up and code simply. Since we are using Spring MVC for web development, Spring Data seems quite suitable for integration.
However, I heard that Cassandra would have better performance in write and read, especially in large scaling system. I am not sure whether it is worth to move to Cassandra and not sure how to measure the performance between MongoDB and Cassandra.
Here are some requirements for my system:
focusing on article fetching
tagging for articles for users to easily search for their favors or related articles
non-distributed system, but have load-balancing and fail-over
Java based, Spring MVC for web development
articles would be stored as XML
probably provide user-defined tables (collections) and fields (keys)
Therefore I would like to raise some questions:
Which Database is the most suitable for my case? You may also raise other databases apart from MongoDB and Cassandra.
If I use Cassandra, which framework would be suitable for integrating to Spring MVC?
Thank you so much in advanced.
I have experience using Spring and Cassandra together. But I always have written my own data access layer.
Using the ORMs out there for Cassandra will not allow you to leverage its full power, and you will, most likely, introduce bugs because your SQL background will make you expect certain behaviours that are just not what Cassandra will give you.
My advice write the code that will access Cassandra yourself and do not be afraid to denormalize A LOT. Think more about how you want to query (or find it) your data than the format in which you want to save it.
I also strongly recommend reading this amazing article: Cassandra Data Modeling Best Practices part 1 part 2
Another DB which might suit your application better is CouchDB (I like using BigCouch). It is another Document based NoSQL database and is in my opinion superior to MongoDB. It offers better solution for scaling and gives emphasis to Availability (just like Cassandra).
I'd like to point you to this question about the difference between CouchDB and MongoDB.
As far as framework goes Play framework has a lot of plugin to work with NoSQL systems, so you might give it a try. You could try playorm which is the last I experimented on.
EDIT : I forgot to mention Kundera as well as an ORM for Cassandra
Choosing between Cassandra and MongoDB depends on type of storage. MongoDB is primarily for document based storage where you get an edge by having various sql like features.
If you require columnar database with high availability and multi dc replication? go for Cassandra.
http://db-engines.com/en/system/Cassandra%3BHBase%3BMongoDB
I want to write a high scalable web application for selling event tickets. I want to use NoSQL database, like Big Table or MongoDB and Cloud Service like Google App Engine (GAE) or Amazon Elastic Compute Cloud (Amazon EC2)
Is it posible using this type of database to be sure that two client will not be able to buy a ticket for the same place simultaneously? Or may be I will have to use RDBMS database and forget about Google App Engine?
Things like GAE's datastore can still support transactional semantics, for example:
http://code.google.com/appengine/docs/python/datastore/transactions.html
So yes, it is possible to do what you're seeking to do. (Note - GAE's Datastore is not exactly NoSQL, since it uses SQL-like queries.)
I have a problem with this question. Not all NoSQL databases are created equally, and different NoSQL databases have different ways they store data. Generally the thing you should be worried about are: data is actually written to disk and not just into memory. Most NoSQL databases can do this but not by default. Let's just say this is not a problem, you can usually tell the database like MOngo or Cassandra to write data to disk, can even tell how many servers at minimum the data should be written to.
The problem is that you may not get a true transactional support. When you deal with ecommerce it's important to have all or nothing type of transation where several operations either succeed completely or rolled back. There must be absolutely no chance that only part of your data is saved. For example, if you need to write data to more than one table (collection or document in NoSQL lingo), if server goes down in the middle of the process and your data is only written to one table, that's usually unacceptable in ecommerce.
I am not familiar with all NoSQL databases, but the ones I know don't have this option yet.
MySQL, on the other hand, does.
If transactional support or lack of it does not bother you, then I think its OK to use NoSQL as long as you tell it to save data to disk and not just into memory.
The answer is 'maybe.'
Depending on what you're trying to build, you many be able to use some of the techniques in this post:
http://kylebanker.com/blog/2010/06/07/mongodb-inventory-transactions/
Using something like get_or_insert you can easily ensure that two clients are not receiving the same resource simultaneously on Google App Engine. However, there are big differences between GAE and a RDBMS, so make sure you study them further before you make a decision.
I've prototyped an iPhone app that uses (internally) SQLite as its data base. The intent was to ultimately have it communicate with a server via PHP, which would use MySQL as the back-end database.
I just discovered Google App Engine, however, but know very little about it. I think it'd be nice to use the Python interface to write to the data store - but I know very little about GQL's capability. I've basically written all the working database code using MySQL, testing internally on the iPhone with SQLite. Will GQL offer the same functionality that SQL can? I read on the site that it doesn't support join queries. Also is it truly relational?
Basically I guess my question is can an app that typically uses SQL backend work just as well with Google's App Engine, with GQL?
I hope that's clear... any guidance is great.
True, Google App Engine is a very cool product, but the datastore is a different beast than a regular mySQL database. That's not to say that what you need can't be done with the GAE datastore; however it may take some reworking on your end.
The most prominent different that you notice right off the start is that GAE uses an object-relational mapping for its data storage scheme. Essentially object graphs are persisted in the database, maintaining there attributes and relationships to other objects. In many cases ORM (object relational mappings) map fairly well on top of a relational database (this is how Hibernate works). The mapping is not perfect though and you will find that you need to make alterations to persist your data. Also, GAE has some unique contraints that complicate things a bit. One contraint that bothers me a lot is not being able to query for attribute paths: e.g. "select ... where dog.owner.name = 'bob' ". It is these rules that force you to read and understand how GAE data store works before you jump in.
I think GAE could work well in your situation. It just may take some time to understand ORM persistence in general, and GAE datastore in specifics.
GQL offers almost no functionality at all; it's only used for SELECT queries, and it only exists to make writing SELECT queries easier for SQL programmers. Behind the scenes, it converts your queries to db.Query objects.
The App Engine datastore isn't a relational database at all. You can do some stuff that looks relational, but my advice for anyone coming from an SQL background is to avoid GQL at all costs to avoid the trap of thinking the datastore is anything at all like an RDBMS, and to forget everything you know about database design. Specifically, if you're normalizing anything, you'll soon wish you hadn't.
I think this article should help you.
Summary: Cloud computing and software development for handheld devices are two very hot technologies that are increasingly being combined to create hybrid solutions. With this article, learn how to connect Google App Engine, Google's cloud computing offering, with the iPhone, Apple's mobile platform. You'll also see how to use the open source library, TouchEngine, to dynamically control application data on the iPhone by connecting to the App Engine cloud and caching that data for offline use.
That's a pretty generic question :)
Short answer: yes. It's going to involve some rethinking of your data model, but yes, changes are you can support it with the GAE Datastore API.
When you create your Python models (think of these as tables), you can certainly define references to other models (so now we have a foreign key). When you select this model, you'll get back the referencing models (pretty much like a join).
It'll most likely work, but it's not a drop in replacement for a mySQL server.