Each key uniquely identifies each item.Īpart from the Amazon employees, not many of us know much about the exact nature of DynamoDB. Every DynamoDB query is executed with the help of a primary key which is identified by the user. Apart from that, it also allows graphs, documents, columnar among its data model.Ī user first stores the data in DynamoDB tables and then interacts with it through PUT and GET queries which are write and read operations respectively.ĭynamoDB supports conditional operations and basic CRUD operations. The data is stored on solid-state drives which offer high I/O performance along with efficiently handling high-scale requests.ĭynamoDB uses a NoSQL database model which is nonrelational. Furthermore, it can also serve any level of request traffic.
DynamoDB is known for its scalability and latencies.Īs per AWS, DynamoDB cuts cost and makes it easy to store and retrieve any amount of data. So, without any further ado, let’s begin.ĭynamoDB which is also known as Amazon Dynamo Database or DDB is a NoSQL database service provided by Amazon Web Services.
#AWS LOCAL DYNAMODB CONSOLE HOW TO#
resource "aws_dynamodb_table" "table" ,ĭeleteInput := &dynamodb.We’ll also provide you with a detailed tutorial on how to set up your own DynamoDB database locally.
#AWS LOCAL DYNAMODB CONSOLE CODE#
The following Terraform code creates the stuffed-animals table. The basic table architecture is configured with Terraform, along with a few items. The table represents stuffed animals, and is appropriately named stuffed-animals. The DynamoDB prototype I created consists of a single table with a primary key and a global secondary index. I have yet to see how well it scales up for large datasets, but for prototyping and small applications it seems like a really nice option. My first impression of DynamoDB is that it's very easy to use, especially for those with MongoDB experience. To build a secondary index, DynamoDB must maintain an additional read-only projection of the table, which adds to service costs 8. While global secondary indexes are extremely useful, they are not free. A global secondary index creates an index with a partition key and sort key other than the ones assigned to the table, while a local secondary index creates an index with a partition key matching the one assigned to the table, but with a different sort key 7. There are two types of secondary indexes: global secondary indexes and local secondary indexes. Secondary indexes allow for attributes other than the primary keys to be queried. This makes secondary indexes in DynamoDB very important. In contrast, relational database tables can be queried using any of their columns, no matter if they are a primary key, indexed or otherwise. One difference between DynamoDB and traditional SQL relational databases is that in DynamoDB, queries of tables can only be performed on attributes that are primary keys or secondary indexes. In addition to primary keys, DynamoDB tables can have secondary indexes. Partition keys and sort keys also help DynamoDB with its internal storage of table data 6. In a composite key, the combination of the partition key attribute and sort key attribute must be unique for each item in the table.
If a table has a partition key and a sort key, this is called a composite key. If a table only has a partition key, each item in the table must have a unique value for that partition key attribute. Partition keys and sort keys are assigned to attributes in a table.
There are two types of primary keys: partition keys and sort keys. A DynamoDB scalar is roughly equivalent to a MongoDB field.ĭynamoDB tables are required to have a primary key, and can optionally have one or more secondary indexes.
Document types are JSON documents, containing objects and arrays. Scalar types include primitive data types such as strings, numbers, and booleans. Attributes can have three types of values: scalar, document, and set 5. Attributes are the most fundamental building block of data in DynamoDB. A DynamoDB attribute is a name-value pair that exists on an item.