I've just figured out a big mistake I had while creating the dynamodb structure. I've created 11 tables, whereas one of them is the table mostly refereed to and the others are complementary tables. For example, I have a table where I hold names (together with other info) called "Names" and another table called "NamesMappings" holding all these names added to the "Names" table so that each time a user wants to add a name to the "Names" table he first tries to put the name in "NamesMappings" and only if it succeed (therefore this name doesn't exist) he can add the name into the "Names" table. This procedure helps if the name is not unique and is not the primary key in the "Names" table and with this technique I don't have to search inside the "Names" table if the name exists, but instead I can try to add it to the "NamesMappings" table and only if it succeed I know this is a unique name.
First of all, I would like to ask you if this is a common approach or there is a better one?
Next, I figured out that with this design I soon reached to 11 tables each has 5 provisioned capacity of read and write which leads to overall 55 provisioned read and write under the free-tier. Then I understood why I get all these payments each month, because as the number of tables is getting bigger, and I leave the provisioned capacity as default (both read/write capacity are 5) I get more and more provisioned capacity.
So, what should be my conclusion from this understanding? Should I try to reduce the number of tables even if it takes more effort to preform scanning and querying inside the table? Or should I split the table same as I do but reduce the capacity of these mappings tables used only for indication if an item exists or not in another table?
If I understand your problem correctly you're missing the whole concept of NoSQL Databases.
Your Names
table should have a Hash key (which is similar to a Primary key) that has a uniformly generated identifier (an UUID is a great candidate). This would automatically make this Table queryable by this unique identifier. You said, however, that you don't know the ID but you only know the Name instead. This leads me to think you could create a Global Secondary Index (GSI) on the Name
attribute inside the Names
table so you can also query by Name
. Up to this point, your table structure should look like this:
id | name
Both of them are independently queryable, which gives you a lot of flexibility already.
Now, let's say you want to add the NameMapping
attribute (which I don't know how it looks like), you can simply add it under the Names
table, getting rid of the NamesMappings
table, greatly reducing the number of WCUs and RCUs across your account. Your table structure should now look like this:
id | name | mappings
where mappings
is, let's say, a JSON object.
Since you can only query on top level attributes in DynamoDB, you can now perform a query against the name
attribute which has a GSI configured. If the query returns nothing, then name
is unique. But let's say you still need some data inside the mappings
object, then you could query by name
and, in your code, you could apply a map/filter/reduce operation on the mappings
attribute and decide what to do next.
Remember that duplication is just OK in a NoSQL world. This may look scary if you come from a purely SQL background, but data should be stored in such a way in NoSQL databases that you should be able to fetch all the needed information in one go, therefore avoiding "joins" (joins are still possible in a NoSQL database, but since there are no strong relationships between entities, you need to perform these joins manually on the code level). To give you some real context, imagine you have a Orders
table where you keep track of the ordered Products and the Store that the Order belongs to: you'd save both the Products and the Store objects (and not their IDs, as it would happen in the SQL way) inside the Order object, so if you want to query for a given OrderId in the future, you wouldn't need to make extra calls (aka "joins") to the Product/Store tables to fetch the information, since everything would already be stored inside the Order object.