NoSQL Use Case Scenarios or WHEN to use NoSQL [closed]












204














With all the hype it seems really hard to find reliable information on when to use this. So I pose the following questions, and I'm sorry if these are really dumb questions in advance:




  1. Should I use NoSQL for user data? E.g. profiles, usernames + passwords, etc.

  2. Should I use NoSQL for important content? E.g. articles, blog posts, product inventory, etc.


I'm assuming no? And I feel like NoSQL is just for quickly accessible things from which it's OK to lose data. But I also read that NoSQL apps have built-in redundancy so that I don't lose data?



Also if the above 2 examples are bad, could you give me specific business use cases where I would use NoSQL? I see a lot of general descriptions but not a lot of real-world examples. The only things I can think of are user-to-user messaging and analytics.



Thanks!










share|improve this question















closed as primarily opinion-based by aquavitae, Bull, Frédéric Hamidi, Maerlyn, rckoenes Dec 4 '13 at 8:55


Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center, please edit the question.




















    204














    With all the hype it seems really hard to find reliable information on when to use this. So I pose the following questions, and I'm sorry if these are really dumb questions in advance:




    1. Should I use NoSQL for user data? E.g. profiles, usernames + passwords, etc.

    2. Should I use NoSQL for important content? E.g. articles, blog posts, product inventory, etc.


    I'm assuming no? And I feel like NoSQL is just for quickly accessible things from which it's OK to lose data. But I also read that NoSQL apps have built-in redundancy so that I don't lose data?



    Also if the above 2 examples are bad, could you give me specific business use cases where I would use NoSQL? I see a lot of general descriptions but not a lot of real-world examples. The only things I can think of are user-to-user messaging and analytics.



    Thanks!










    share|improve this question















    closed as primarily opinion-based by aquavitae, Bull, Frédéric Hamidi, Maerlyn, rckoenes Dec 4 '13 at 8:55


    Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center, please edit the question.


















      204












      204








      204


      58





      With all the hype it seems really hard to find reliable information on when to use this. So I pose the following questions, and I'm sorry if these are really dumb questions in advance:




      1. Should I use NoSQL for user data? E.g. profiles, usernames + passwords, etc.

      2. Should I use NoSQL for important content? E.g. articles, blog posts, product inventory, etc.


      I'm assuming no? And I feel like NoSQL is just for quickly accessible things from which it's OK to lose data. But I also read that NoSQL apps have built-in redundancy so that I don't lose data?



      Also if the above 2 examples are bad, could you give me specific business use cases where I would use NoSQL? I see a lot of general descriptions but not a lot of real-world examples. The only things I can think of are user-to-user messaging and analytics.



      Thanks!










      share|improve this question















      With all the hype it seems really hard to find reliable information on when to use this. So I pose the following questions, and I'm sorry if these are really dumb questions in advance:




      1. Should I use NoSQL for user data? E.g. profiles, usernames + passwords, etc.

      2. Should I use NoSQL for important content? E.g. articles, blog posts, product inventory, etc.


      I'm assuming no? And I feel like NoSQL is just for quickly accessible things from which it's OK to lose data. But I also read that NoSQL apps have built-in redundancy so that I don't lose data?



      Also if the above 2 examples are bad, could you give me specific business use cases where I would use NoSQL? I see a lot of general descriptions but not a lot of real-world examples. The only things I can think of are user-to-user messaging and analytics.



      Thanks!







      nosql use-case






      share|improve this question















      share|improve this question













      share|improve this question




      share|improve this question








      edited Nov 15 '17 at 11:11









      Shimmy

      49.2k101335541




      49.2k101335541










      asked May 11 '12 at 14:59









      user1389722

      1,026284




      1,026284




      closed as primarily opinion-based by aquavitae, Bull, Frédéric Hamidi, Maerlyn, rckoenes Dec 4 '13 at 8:55


      Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center, please edit the question.






      closed as primarily opinion-based by aquavitae, Bull, Frédéric Hamidi, Maerlyn, rckoenes Dec 4 '13 at 8:55


      Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center, please edit the question.


























          2 Answers
          2






          active

          oldest

          votes


















          150














          It really is an "it depends" kinda question. Some general points:




          • NoSQL is typically good for unstructured/"schemaless" data - usually, you don't need to explicitly define your schema up front and can just include new fields without any ceremony

          • NoSQL typically favours a denormalised schema due to no support for JOINs per the RDBMS world. So you would usually have a flattened, denormalized representation of your data.

          • Using NoSQL doesn't mean you could lose data. Different DBs have different strategies. e.g. MongoDB - you can essentially choose what level to trade off performance vs potential for data loss - best performance = greater scope for data loss.

          • It's often very easy to scale out NoSQL solutions. Adding more nodes to replicate data to is one way to a) offer more scalability and b) offer more protection against data loss if one node goes down. But again, depends on the NoSQL DB/configuration. NoSQL does not necessarily mean "data loss" like you infer.

          • IMHO, complex/dynamic queries/reporting are best served from an RDBMS. Often the query functionality for a NoSQL DB is limited.

          • It doesn't have to be a 1 or the other choice. My experience has been using RDBMS in conjunction with NoSQL for certain use cases.

          • NoSQL DBs often lack the ability to perform atomic operations across multiple "tables".


          You really need to look at and understand what the various types of NoSQL stores are, and how they go about providing scalability/data security etc. It's difficult to give an across-the-board answer as they really are all different and tackle things differently.



          For MongoDb as an example, check out their Use Cases to see what they suggest as being "well suited" and "less well suited" uses of MongoDb.






          share|improve this answer



















          • 9




            The claim about NoSQL not supporting joins is misleading. Some NoSQL databases are actually far better at joins than relational databases. Some don't support them at all. This answer seems to be more about MongoDB in particular than about NoSQL in general.
            – Alan Plum
            Feb 25 '15 at 10:26






          • 1




            Great summary. @AlanPlum, what specific NoSQL databases are you referring to?
            – brian
            May 18 '16 at 1:11






          • 2




            @brian I'm a contributor to ArangoDB (arangodb.com), which is a mix of a document database (think MongoDB) and a graph database (think Neo4J) with not only cheap joins but also real transactions. That said, NoSQL databases are not a homogeneous group and it's impossible to generalize from any one NoSQL database to the entire "category".
            – Alan Plum
            May 24 '16 at 11:38



















          8














          I think Nosql is "more suitable" in these scenarios at least (more supplementary is welcome)




          1. Easy to scale by just adding more nodes.



          2. Query on large data set



            Imagine tons of tweets posted on twitter every day. In RDMS, there could be tables with millions (or billions?) of rows, and you don't want to do query on those tables directly, not even mentioning, most of time, table joins are also needed for complex queries.




          3. Disk I/O bottleneck



            If a website needs to send results to different users based on users' real-time info, we are probably talking about tens or hundreds of thousands of SQL read/write requests per second. Then disk i/o will be a serious bottleneck.








          share|improve this answer



















          • 18




            I don't understand what could be problem with RDBMS for #2. And NoSQL have less disk I/O as per #3?
            – avi
            Jun 30 '14 at 6:46






          • 5




            As @avi says, I think there's no problem for #2 as long as you query the tables over the index. Millions of rows? Ok, retrieve only the indexes I wanna use
            – Xtreme Biker
            Mar 31 '15 at 8:41






          • 10




            #2 and 3 are both false. For 2, I've done performance tests on importing/exporting data and seen SQL Server 2014 crush Mongo on large data imports and exports. For 3, strongly typed data in SQL typically takes (I've seen over 50% before compression) up much less space than document databases.
            – brian
            May 18 '16 at 1:04






          • 6




            Yeah, and even for #1, I just don´t get it. Scaling up is part of the clustering contract all major rdbms propose
            – Sebas
            Feb 8 '17 at 12:03


















          2 Answers
          2






          active

          oldest

          votes








          2 Answers
          2






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          150














          It really is an "it depends" kinda question. Some general points:




          • NoSQL is typically good for unstructured/"schemaless" data - usually, you don't need to explicitly define your schema up front and can just include new fields without any ceremony

          • NoSQL typically favours a denormalised schema due to no support for JOINs per the RDBMS world. So you would usually have a flattened, denormalized representation of your data.

          • Using NoSQL doesn't mean you could lose data. Different DBs have different strategies. e.g. MongoDB - you can essentially choose what level to trade off performance vs potential for data loss - best performance = greater scope for data loss.

          • It's often very easy to scale out NoSQL solutions. Adding more nodes to replicate data to is one way to a) offer more scalability and b) offer more protection against data loss if one node goes down. But again, depends on the NoSQL DB/configuration. NoSQL does not necessarily mean "data loss" like you infer.

          • IMHO, complex/dynamic queries/reporting are best served from an RDBMS. Often the query functionality for a NoSQL DB is limited.

          • It doesn't have to be a 1 or the other choice. My experience has been using RDBMS in conjunction with NoSQL for certain use cases.

          • NoSQL DBs often lack the ability to perform atomic operations across multiple "tables".


          You really need to look at and understand what the various types of NoSQL stores are, and how they go about providing scalability/data security etc. It's difficult to give an across-the-board answer as they really are all different and tackle things differently.



          For MongoDb as an example, check out their Use Cases to see what they suggest as being "well suited" and "less well suited" uses of MongoDb.






          share|improve this answer



















          • 9




            The claim about NoSQL not supporting joins is misleading. Some NoSQL databases are actually far better at joins than relational databases. Some don't support them at all. This answer seems to be more about MongoDB in particular than about NoSQL in general.
            – Alan Plum
            Feb 25 '15 at 10:26






          • 1




            Great summary. @AlanPlum, what specific NoSQL databases are you referring to?
            – brian
            May 18 '16 at 1:11






          • 2




            @brian I'm a contributor to ArangoDB (arangodb.com), which is a mix of a document database (think MongoDB) and a graph database (think Neo4J) with not only cheap joins but also real transactions. That said, NoSQL databases are not a homogeneous group and it's impossible to generalize from any one NoSQL database to the entire "category".
            – Alan Plum
            May 24 '16 at 11:38
















          150














          It really is an "it depends" kinda question. Some general points:




          • NoSQL is typically good for unstructured/"schemaless" data - usually, you don't need to explicitly define your schema up front and can just include new fields without any ceremony

          • NoSQL typically favours a denormalised schema due to no support for JOINs per the RDBMS world. So you would usually have a flattened, denormalized representation of your data.

          • Using NoSQL doesn't mean you could lose data. Different DBs have different strategies. e.g. MongoDB - you can essentially choose what level to trade off performance vs potential for data loss - best performance = greater scope for data loss.

          • It's often very easy to scale out NoSQL solutions. Adding more nodes to replicate data to is one way to a) offer more scalability and b) offer more protection against data loss if one node goes down. But again, depends on the NoSQL DB/configuration. NoSQL does not necessarily mean "data loss" like you infer.

          • IMHO, complex/dynamic queries/reporting are best served from an RDBMS. Often the query functionality for a NoSQL DB is limited.

          • It doesn't have to be a 1 or the other choice. My experience has been using RDBMS in conjunction with NoSQL for certain use cases.

          • NoSQL DBs often lack the ability to perform atomic operations across multiple "tables".


          You really need to look at and understand what the various types of NoSQL stores are, and how they go about providing scalability/data security etc. It's difficult to give an across-the-board answer as they really are all different and tackle things differently.



          For MongoDb as an example, check out their Use Cases to see what they suggest as being "well suited" and "less well suited" uses of MongoDb.






          share|improve this answer



















          • 9




            The claim about NoSQL not supporting joins is misleading. Some NoSQL databases are actually far better at joins than relational databases. Some don't support them at all. This answer seems to be more about MongoDB in particular than about NoSQL in general.
            – Alan Plum
            Feb 25 '15 at 10:26






          • 1




            Great summary. @AlanPlum, what specific NoSQL databases are you referring to?
            – brian
            May 18 '16 at 1:11






          • 2




            @brian I'm a contributor to ArangoDB (arangodb.com), which is a mix of a document database (think MongoDB) and a graph database (think Neo4J) with not only cheap joins but also real transactions. That said, NoSQL databases are not a homogeneous group and it's impossible to generalize from any one NoSQL database to the entire "category".
            – Alan Plum
            May 24 '16 at 11:38














          150












          150








          150






          It really is an "it depends" kinda question. Some general points:




          • NoSQL is typically good for unstructured/"schemaless" data - usually, you don't need to explicitly define your schema up front and can just include new fields without any ceremony

          • NoSQL typically favours a denormalised schema due to no support for JOINs per the RDBMS world. So you would usually have a flattened, denormalized representation of your data.

          • Using NoSQL doesn't mean you could lose data. Different DBs have different strategies. e.g. MongoDB - you can essentially choose what level to trade off performance vs potential for data loss - best performance = greater scope for data loss.

          • It's often very easy to scale out NoSQL solutions. Adding more nodes to replicate data to is one way to a) offer more scalability and b) offer more protection against data loss if one node goes down. But again, depends on the NoSQL DB/configuration. NoSQL does not necessarily mean "data loss" like you infer.

          • IMHO, complex/dynamic queries/reporting are best served from an RDBMS. Often the query functionality for a NoSQL DB is limited.

          • It doesn't have to be a 1 or the other choice. My experience has been using RDBMS in conjunction with NoSQL for certain use cases.

          • NoSQL DBs often lack the ability to perform atomic operations across multiple "tables".


          You really need to look at and understand what the various types of NoSQL stores are, and how they go about providing scalability/data security etc. It's difficult to give an across-the-board answer as they really are all different and tackle things differently.



          For MongoDb as an example, check out their Use Cases to see what they suggest as being "well suited" and "less well suited" uses of MongoDb.






          share|improve this answer














          It really is an "it depends" kinda question. Some general points:




          • NoSQL is typically good for unstructured/"schemaless" data - usually, you don't need to explicitly define your schema up front and can just include new fields without any ceremony

          • NoSQL typically favours a denormalised schema due to no support for JOINs per the RDBMS world. So you would usually have a flattened, denormalized representation of your data.

          • Using NoSQL doesn't mean you could lose data. Different DBs have different strategies. e.g. MongoDB - you can essentially choose what level to trade off performance vs potential for data loss - best performance = greater scope for data loss.

          • It's often very easy to scale out NoSQL solutions. Adding more nodes to replicate data to is one way to a) offer more scalability and b) offer more protection against data loss if one node goes down. But again, depends on the NoSQL DB/configuration. NoSQL does not necessarily mean "data loss" like you infer.

          • IMHO, complex/dynamic queries/reporting are best served from an RDBMS. Often the query functionality for a NoSQL DB is limited.

          • It doesn't have to be a 1 or the other choice. My experience has been using RDBMS in conjunction with NoSQL for certain use cases.

          • NoSQL DBs often lack the ability to perform atomic operations across multiple "tables".


          You really need to look at and understand what the various types of NoSQL stores are, and how they go about providing scalability/data security etc. It's difficult to give an across-the-board answer as they really are all different and tackle things differently.



          For MongoDb as an example, check out their Use Cases to see what they suggest as being "well suited" and "less well suited" uses of MongoDb.







          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited Nov 15 '17 at 11:17









          Shimmy

          49.2k101335541




          49.2k101335541










          answered May 11 '12 at 15:21









          AdaTheDev

          105k22163173




          105k22163173








          • 9




            The claim about NoSQL not supporting joins is misleading. Some NoSQL databases are actually far better at joins than relational databases. Some don't support them at all. This answer seems to be more about MongoDB in particular than about NoSQL in general.
            – Alan Plum
            Feb 25 '15 at 10:26






          • 1




            Great summary. @AlanPlum, what specific NoSQL databases are you referring to?
            – brian
            May 18 '16 at 1:11






          • 2




            @brian I'm a contributor to ArangoDB (arangodb.com), which is a mix of a document database (think MongoDB) and a graph database (think Neo4J) with not only cheap joins but also real transactions. That said, NoSQL databases are not a homogeneous group and it's impossible to generalize from any one NoSQL database to the entire "category".
            – Alan Plum
            May 24 '16 at 11:38














          • 9




            The claim about NoSQL not supporting joins is misleading. Some NoSQL databases are actually far better at joins than relational databases. Some don't support them at all. This answer seems to be more about MongoDB in particular than about NoSQL in general.
            – Alan Plum
            Feb 25 '15 at 10:26






          • 1




            Great summary. @AlanPlum, what specific NoSQL databases are you referring to?
            – brian
            May 18 '16 at 1:11






          • 2




            @brian I'm a contributor to ArangoDB (arangodb.com), which is a mix of a document database (think MongoDB) and a graph database (think Neo4J) with not only cheap joins but also real transactions. That said, NoSQL databases are not a homogeneous group and it's impossible to generalize from any one NoSQL database to the entire "category".
            – Alan Plum
            May 24 '16 at 11:38








          9




          9




          The claim about NoSQL not supporting joins is misleading. Some NoSQL databases are actually far better at joins than relational databases. Some don't support them at all. This answer seems to be more about MongoDB in particular than about NoSQL in general.
          – Alan Plum
          Feb 25 '15 at 10:26




          The claim about NoSQL not supporting joins is misleading. Some NoSQL databases are actually far better at joins than relational databases. Some don't support them at all. This answer seems to be more about MongoDB in particular than about NoSQL in general.
          – Alan Plum
          Feb 25 '15 at 10:26




          1




          1




          Great summary. @AlanPlum, what specific NoSQL databases are you referring to?
          – brian
          May 18 '16 at 1:11




          Great summary. @AlanPlum, what specific NoSQL databases are you referring to?
          – brian
          May 18 '16 at 1:11




          2




          2




          @brian I'm a contributor to ArangoDB (arangodb.com), which is a mix of a document database (think MongoDB) and a graph database (think Neo4J) with not only cheap joins but also real transactions. That said, NoSQL databases are not a homogeneous group and it's impossible to generalize from any one NoSQL database to the entire "category".
          – Alan Plum
          May 24 '16 at 11:38




          @brian I'm a contributor to ArangoDB (arangodb.com), which is a mix of a document database (think MongoDB) and a graph database (think Neo4J) with not only cheap joins but also real transactions. That said, NoSQL databases are not a homogeneous group and it's impossible to generalize from any one NoSQL database to the entire "category".
          – Alan Plum
          May 24 '16 at 11:38













          8














          I think Nosql is "more suitable" in these scenarios at least (more supplementary is welcome)




          1. Easy to scale by just adding more nodes.



          2. Query on large data set



            Imagine tons of tweets posted on twitter every day. In RDMS, there could be tables with millions (or billions?) of rows, and you don't want to do query on those tables directly, not even mentioning, most of time, table joins are also needed for complex queries.




          3. Disk I/O bottleneck



            If a website needs to send results to different users based on users' real-time info, we are probably talking about tens or hundreds of thousands of SQL read/write requests per second. Then disk i/o will be a serious bottleneck.








          share|improve this answer



















          • 18




            I don't understand what could be problem with RDBMS for #2. And NoSQL have less disk I/O as per #3?
            – avi
            Jun 30 '14 at 6:46






          • 5




            As @avi says, I think there's no problem for #2 as long as you query the tables over the index. Millions of rows? Ok, retrieve only the indexes I wanna use
            – Xtreme Biker
            Mar 31 '15 at 8:41






          • 10




            #2 and 3 are both false. For 2, I've done performance tests on importing/exporting data and seen SQL Server 2014 crush Mongo on large data imports and exports. For 3, strongly typed data in SQL typically takes (I've seen over 50% before compression) up much less space than document databases.
            – brian
            May 18 '16 at 1:04






          • 6




            Yeah, and even for #1, I just don´t get it. Scaling up is part of the clustering contract all major rdbms propose
            – Sebas
            Feb 8 '17 at 12:03
















          8














          I think Nosql is "more suitable" in these scenarios at least (more supplementary is welcome)




          1. Easy to scale by just adding more nodes.



          2. Query on large data set



            Imagine tons of tweets posted on twitter every day. In RDMS, there could be tables with millions (or billions?) of rows, and you don't want to do query on those tables directly, not even mentioning, most of time, table joins are also needed for complex queries.




          3. Disk I/O bottleneck



            If a website needs to send results to different users based on users' real-time info, we are probably talking about tens or hundreds of thousands of SQL read/write requests per second. Then disk i/o will be a serious bottleneck.








          share|improve this answer



















          • 18




            I don't understand what could be problem with RDBMS for #2. And NoSQL have less disk I/O as per #3?
            – avi
            Jun 30 '14 at 6:46






          • 5




            As @avi says, I think there's no problem for #2 as long as you query the tables over the index. Millions of rows? Ok, retrieve only the indexes I wanna use
            – Xtreme Biker
            Mar 31 '15 at 8:41






          • 10




            #2 and 3 are both false. For 2, I've done performance tests on importing/exporting data and seen SQL Server 2014 crush Mongo on large data imports and exports. For 3, strongly typed data in SQL typically takes (I've seen over 50% before compression) up much less space than document databases.
            – brian
            May 18 '16 at 1:04






          • 6




            Yeah, and even for #1, I just don´t get it. Scaling up is part of the clustering contract all major rdbms propose
            – Sebas
            Feb 8 '17 at 12:03














          8












          8








          8






          I think Nosql is "more suitable" in these scenarios at least (more supplementary is welcome)




          1. Easy to scale by just adding more nodes.



          2. Query on large data set



            Imagine tons of tweets posted on twitter every day. In RDMS, there could be tables with millions (or billions?) of rows, and you don't want to do query on those tables directly, not even mentioning, most of time, table joins are also needed for complex queries.




          3. Disk I/O bottleneck



            If a website needs to send results to different users based on users' real-time info, we are probably talking about tens or hundreds of thousands of SQL read/write requests per second. Then disk i/o will be a serious bottleneck.








          share|improve this answer














          I think Nosql is "more suitable" in these scenarios at least (more supplementary is welcome)




          1. Easy to scale by just adding more nodes.



          2. Query on large data set



            Imagine tons of tweets posted on twitter every day. In RDMS, there could be tables with millions (or billions?) of rows, and you don't want to do query on those tables directly, not even mentioning, most of time, table joins are also needed for complex queries.




          3. Disk I/O bottleneck



            If a website needs to send results to different users based on users' real-time info, we are probably talking about tens or hundreds of thousands of SQL read/write requests per second. Then disk i/o will be a serious bottleneck.









          share|improve this answer














          share|improve this answer



          share|improve this answer








          edited Nov 15 '17 at 11:18









          Shimmy

          49.2k101335541




          49.2k101335541










          answered Jun 17 '13 at 19:57









          otm

          379416




          379416








          • 18




            I don't understand what could be problem with RDBMS for #2. And NoSQL have less disk I/O as per #3?
            – avi
            Jun 30 '14 at 6:46






          • 5




            As @avi says, I think there's no problem for #2 as long as you query the tables over the index. Millions of rows? Ok, retrieve only the indexes I wanna use
            – Xtreme Biker
            Mar 31 '15 at 8:41






          • 10




            #2 and 3 are both false. For 2, I've done performance tests on importing/exporting data and seen SQL Server 2014 crush Mongo on large data imports and exports. For 3, strongly typed data in SQL typically takes (I've seen over 50% before compression) up much less space than document databases.
            – brian
            May 18 '16 at 1:04






          • 6




            Yeah, and even for #1, I just don´t get it. Scaling up is part of the clustering contract all major rdbms propose
            – Sebas
            Feb 8 '17 at 12:03














          • 18




            I don't understand what could be problem with RDBMS for #2. And NoSQL have less disk I/O as per #3?
            – avi
            Jun 30 '14 at 6:46






          • 5




            As @avi says, I think there's no problem for #2 as long as you query the tables over the index. Millions of rows? Ok, retrieve only the indexes I wanna use
            – Xtreme Biker
            Mar 31 '15 at 8:41






          • 10




            #2 and 3 are both false. For 2, I've done performance tests on importing/exporting data and seen SQL Server 2014 crush Mongo on large data imports and exports. For 3, strongly typed data in SQL typically takes (I've seen over 50% before compression) up much less space than document databases.
            – brian
            May 18 '16 at 1:04






          • 6




            Yeah, and even for #1, I just don´t get it. Scaling up is part of the clustering contract all major rdbms propose
            – Sebas
            Feb 8 '17 at 12:03








          18




          18




          I don't understand what could be problem with RDBMS for #2. And NoSQL have less disk I/O as per #3?
          – avi
          Jun 30 '14 at 6:46




          I don't understand what could be problem with RDBMS for #2. And NoSQL have less disk I/O as per #3?
          – avi
          Jun 30 '14 at 6:46




          5




          5




          As @avi says, I think there's no problem for #2 as long as you query the tables over the index. Millions of rows? Ok, retrieve only the indexes I wanna use
          – Xtreme Biker
          Mar 31 '15 at 8:41




          As @avi says, I think there's no problem for #2 as long as you query the tables over the index. Millions of rows? Ok, retrieve only the indexes I wanna use
          – Xtreme Biker
          Mar 31 '15 at 8:41




          10




          10




          #2 and 3 are both false. For 2, I've done performance tests on importing/exporting data and seen SQL Server 2014 crush Mongo on large data imports and exports. For 3, strongly typed data in SQL typically takes (I've seen over 50% before compression) up much less space than document databases.
          – brian
          May 18 '16 at 1:04




          #2 and 3 are both false. For 2, I've done performance tests on importing/exporting data and seen SQL Server 2014 crush Mongo on large data imports and exports. For 3, strongly typed data in SQL typically takes (I've seen over 50% before compression) up much less space than document databases.
          – brian
          May 18 '16 at 1:04




          6




          6




          Yeah, and even for #1, I just don´t get it. Scaling up is part of the clustering contract all major rdbms propose
          – Sebas
          Feb 8 '17 at 12:03




          Yeah, and even for #1, I just don´t get it. Scaling up is part of the clustering contract all major rdbms propose
          – Sebas
          Feb 8 '17 at 12:03



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