Some of the applications my team is developing will need range queries.
Are the indexes BTree In Oracle NoSQL Database? In one of the docs, it mentions that it's a "ordered maps".
Does it mean that it can't support range queries?
Please advise.
Yes, Oracle NoSQL Database uses B-trees and supports range queries.
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I am beginner in NoSql databases (I use mongodb), I need your help to translate my schema from relational to NoSql schema.
The main nosql concept is different from the traditional sql (relational ) model. It does not means that's you can't do relations between nosql entities but you should care about your use cases before choosing a nosql database.
In sql , relations are generally done by ids. You can achieve the same with a nosql database.
In nosql, an entry is often call a document. In a document, you could refer to an other doc by given it's id key for example ( as you do already with user_id, group_id .. ).
I suggest you to read the mongoDB doc about data modeling https://docs.mongodb.com/manual/core/data-modeling-introduction/
It could be a nice introduction to what you want to do
What are comparable database like Mongo DB?
We are trying to evaluate Mongo DB and find the best database for a enterprise level application.
Is there any developer UI and admin UI available for MongoDB like SQL Plus/Toad etc for Oracle?
MongoDB is a document-oriented database, so instead of a row of data, you have a document. In MonogDB's case, its a JSON document. Apache's CouchDB is another document database that stores data in JSON format although there are subtle differences between the two.
Choosing between the two depends on your use case. Sometimes CouchDB is better than MongoDB.
Checkout this comparative to see the differences.
MongoDB is what is known as a NoSQL database, which is I assume why you're interested in it. You can find a list of other NoSQL databases at the below links:
http://en.wikipedia.org/wiki/NoSQL
http://nosql-database.org/
MongoDB does not include a GUI-style administrative interface; however, there are numerous community projects that provide admin UIs for MongoDB:
http://www.mongodb.org/display/DOCS/Admin+UIs
I like document oriented databases like MongoDB very much. Because they are shema-less. You can just insert find and update your records without first having to define a schema. But you can define one in your own Project logic. You have more freedom.
It would be nice to have an embeddable NoSQL database. Like SQLite but document oriented.
Currently I do develop one in Java. (You can also use it withhin an Android App):
https://github.com/neo-expert/thingdb
I am quite happy with MongoVue. I've made a couple of videos about this here.
There seem to be a lot of new "NoSQL" type databases out there.
Some of the popular ones are CouchDB, Cassandra and MongoDB.
What are the differences between such databases and how are they different from tradition relational databases? What are the advantages and disadvantages of picking NoSQL DBs over SQL DBs?
The term NoSQL covers a lot of different approaches to data storage ranging from the simplest key/value storage to sophisticated document databases. It's a catchy buzz word, but not very discriptive IMHO.
For a quick intro you could take a look at the Wikipedia entry for NoSQL
Agreed, the question is "not which is better," it's "which solution or set of solutions is best for this particular situation."
NoSQL covers a lot of different storage technologies such as CouchDB, MongoDB, Cassandra and Solr.
CouchDB and MongoDB store multi-dimensional data-structures. MongoDB is also schema-less. Cassandra is a column-based storage engine for fast retrieval, and Solr helps solve other problems such as faceting.
NoSQL simply refers to any storage facility which is not interacted with via SQL queries.
They are not better. NOSQL doesn't involve any new innovation or special feature. NOSQL just refers to a collection of software products that are used for certain types of application but don't necessarily have much else in common with each other. NOSQL does not have to mean a non-relational database.
Folks, Its a hot debate now a days, SQL or NoSQL, While some admire the elegance in terms of performance of NoSQL databases while others want to live with the legacy of SQL or the RDBMS. While each have its merits and demerits ,I tried to contrast it in brief using some points.
While RDBMS uses relations and joins to make data simpler in database tables
NoSQL don't use joins for performance.
NoSQL scales freely when we talk in terms of schema and data, while its very tough to scale a RDBMS if data grows.
There are restriction in size of data in RDBMS in terms of data-types capability, files of any size can be used in NoSQL databases.
Data integrity enforcement comes to play only in RDBMS not in NoSQL databases.
ACID is not the cup of tea for NoSQL databases but for RDBMS.
RDBMS supports complex transactions whereas NoSQL keeps mum for transactions.
NoSQL does not support constraints and validations while its the basic ingredient in RDBMS.
Data is not structured in NoSQL but is highly structured in form of tables in RDBMS.
Its all depends upon the nature and need of the project whether to use SQL or NoSQL.
RDBMS is completely structured way of storing data.
While the NoSQL is unstructured way of storing the data.
And another main difference is that the amount of data stored mainly depends on the Physical memory of the system. While in the NoSQL you don't have any such limits as you can scale the system horizontally.
You'll find that NoSQL database have few common characteristics. They can be roughly divided into a few categories:
key/value stores
Bigtable inspired databases (based on the Google Bigtable paper)
Dynamo inspired databases
distributed databases
document databases
Well,The basic difference are discussed below.Of course,now No-SQL concepts getting popular day by day.But still which one we need to use based on project need or requirements.
1) SQL databases are primarily called as RDBMS. whereas NoSQL database are primarily called as Non-Relational or Distributed database.
2) RDBMS will follow ACID properties i.e Atomcity,Consistency,Isolation,Durability.But in No-Sql it's following CAP (Consistency, Availability and Portioning).
3) In SQL we store data in Tabular formats only.But in No-SQL it uses collection of key-value pair, documents, graph databases or wide-column stores.So No-SQL is Schema free and It can handle structured, semi-structured and unstructured data.
But SQL is not Schema free.SQL is having Pre-Defined schema.i.e In SQL if you have table and in that first column is int data type,then you cant store string or Float values.
4) RDBMS follows SQL ( structured query language ) for defining and manipulating the data, which is very powerful. In NoSQL database, queries are focused on collection of documents. Sometimes it is also called as UnQL (Unstructured Query Language). The syntax of using UnQL varies from database to database.Also SQL databases are good fit for the complex query intensive environment whereas NoSQL databases are not good fit for complex queries. On a high-level, NoSQL don’t have standard interfaces to perform complex queries, and the queries themselves in NoSQL are not as powerful as SQL query language.
For Eg..Take Social Eng. sites,We upload photos/videos/Music/Album..etc.For that we get comments, replies to comments,like..etc.Here we can get numbers,special characters..,so almost we cant predict what might be the reply or comments.In this case we go for No-SQL in documented type like below to store the comments.
{
user_id: ObjectID("65f82bda42e7b8c76f5c1969"),
update: [
{
date: ISODate("2015-09-18T10:02:47.620Z"),
text: "Nice picture."
},
{
date: ISODate("2015-09-17T13:14:20.789Z"),
text: "1234#some smile symbol"
}
{
date: ISODate("2015-09-17T12:33:02.132Z"),
text: "...Oh my god.."
}
]
}
In Above if we go for SQL we cant store comments (text above) in column only.We need to store based on type.So we will end up with Big complex query with number of joins with different tables .But SQL is good for Transactions.
5)In most typical situations, SQL databases are Vertically scalable. You can manage increasing load by increasing the CPU, RAM, SSD, etc, on a single server. On the other hand, No-SQL databases are Horizontally scalable. You can just add few more servers easily in your No-SQL database infrastructure to handle the large traffic.
6)SQL databases are best fit for Heavy duty transnational type applications, as it is more stable and promises the atomicity as well as integrity of the data. While you can use NoSQL for transactions purpose, it is still not comparable and stable enough in high load and for complex transactional applications.
7)Examples for No-SQL are MangoDB,Cassandra..etc while for SQL are MySQL,SQL Server etc..
What "NoSQL" database engines support dynamic / advanced queries in a similar fashion to MongoDB (http://www.mongodb.org/display/DOCS/Advanced+Queries) ?
Specifically interested in options that support ad-hoc querying from a shell or within client languages.
None just use MongoDB ;)
Honestly, it really depends on what type of querying you plan to do. For Key/Value style queries where you plan to just pull up one document at a time, then basically all of the NoSQL DBs are good for this.
When it comes to pulling back "sets" of data or using alternate keys, then MongoDB is probably your best "crossover" here. Many NoSQL DBs have limited querying functions, especially on non-key fields. Of course, that's kind of the point of "Key-Value stores", so Mongo is kind of a mutant here.
The last I checked with Cassandra, there was definitely some "hoop-jumping" involved to really support ad-hoc non-key queries. And CouchDB seems to point to "just Map / Reduce".
That stated, I believe that there is motion from several NoSQL dbs to support such ad-hoc querying mechanism. So this answer could be completely wrong in 2 months :)
So I'm looking to run Sphinx over a NoSQL system such as MongoDB, HBase, Cassandra, etc.
Right now, we're comparing all the NoSQL systems out there. Basically, we need to query 50+ Million rows of product data with fulltext searches thousands of times a second, so we're trying to find the most efficient NoSQL system.
Here is our question, though. If we use any NoSQL system with Sphinx, when we perform the actual searches, will the search have any interaction with the NoSQL system itself, or will Sphinx be doing the work as it has the data indexed? If it's only Sphinx, then wouldn't the performance of the NoSQL system be only secondary?
Thanks!
Using the latest string attribute, you can cut of the database part of the search completely, that will be much more efficient.
As my understanding, I think you can do it. Because I'm only familiar with mongodb and hbase, i can only talk about this question based on the 2 databases. You need to do some work on the indexer and build the data/attributes into the sphinx index file, and to include the primary key(which mark the sole record in the database) into it too(for mongodb, it's object_id, for hbase, it's row key), then after you do the fulltext search, you can get the whole data/attributes from databases by the primary key.
Besides, another full-text search engine supports no-sql db very well, it's solr. you can try it if the performance of it can satisfy your request.