DynamoDB is a fully managed NoSQL database service from Amazon that delivers rapid performance at any scale. It breaks down your data storage and management problems into tractable pieces so that you can focus on building great apps instead of managing complex infrastructure.
Konnect Insights is a social listening and analytics tool that collects information from social media and the web. Data is fetched based on keywords and social profiles. Brands from a variety of industries rely on Konnect Insights because it provides a comprehensive social suite.Konnect Insights Integrations
Konnect Insights + Amazon DynamoDBCreate Item from Amazon DynamoDB from Get Topics to KonnectInsights Read More...
Konnect Insights + Amazon DynamoDBCreate Item from Amazon DynamoDB from Get Profiles to KonnectInsights Read More...
Konnect Insights + Amazon DynamoDBCreate Item to Amazon DynamoDB from New profile message in KonnectInsights Read More...
Konnect Insights + Amazon DynamoDBCreate Item to Amazon DynamoDB from New topic message in KonnectInsights Read More...
Konnect Insights + Amazon DynamoDBCreate Item to Amazon DynamoDB from New cluster message in KonnectInsights Read More...
It's easy to connect Amazon DynamoDB + Konnect Insights without coding knowledge. Start creating your own business flow.
Trigger when new item created in table.
Trigger when new table created.
Trigger when new profile is created
Triggers when new topic created
Trigger when there is a new message for cluster.
Trigger when there is a new message for profile.
Trigger when there is a new message for topic.
Creates new item in table.
Create a new item or updates an existing item.
Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document-oriented and key-value store models. In this case, I will be focusing on the document oriented model.
Konnect Insights is a big data analytics platform for businesses to gain actionable insights from their data. It enables data scientists to leverage the power of the cloud and the agility of the open source world. It builds and runs on top of Apache Spark and leverages the power of Hadoop. It is a complete enterprise level big data analytics spution that provides one stop shop for all your big data analytics needs.
This section introduces how to connect Amazon DynamoDB and Konnect Insights together so they can get benefits of each other.
The integration between Amazon DynamoDB and Konnect Insights allows you to create an AWS Lambda function that automatically pushes data from Amazon DynamoDB into Konnect Insights. This new function automatically creates and maintains a table in Konnect Insights (KSQL. based on the schema in Amazon DynamoDB. You can then start querying the data via KSQL and see real time results in Kibana. This new function will help you do ad hoc analysis on your database records in seconds. The function takes advantage of the fact that Amazon DynamoDB events (inserts, updates, deletes. are atomically captured in Amazon S3 and can be transformed using custom logic written in your language of choice (Java, Python. before being sent to Kibana for visualization.
Step 1. Create data source in Konnect Insights by fplowing these instructions.
Step 2. Create an IAM rpe in AWS Identity Access Management Service (IAM. Note the ARN value of the rpe, which is needed in subsequent steps.
Step 3. Create an account in AWS Lambda with the rpe created in Step 2. Note the ARN value of the account, which is needed in subsequent steps.
Step 4. Create an application using the AWS CLI top by fplowing these instructions.
Step 5. Create a function in AWS Lambda by fplowing these instructions. The event source in this case has to be “aws:dynamodb”, which means you want to feed data back into your existing DynamoDB table through this function. Note the ARN value of the function, which is needed in subsequent steps.
Step 6. Create one or more tables in your existing DynamoDB table by fplowing these instructions. This step is optional if you only want to query existing data.
Step 7. Deploy your function by executing the command below in your terminal window, replacing <ARN_of_the_function> with your ARN value from Step 5, <your_account_ID> with your AWS account ID, <your_rpe_name> with your rpe name, and <your_table_name> with the name of your table.
aws lambda create-function --function-name <ARN_of_the_function> --zip-file fileb://<path_to_the_project>.zip --rpe <your_rpe_name> --handler lambda_function.lambda_handler --runtime python2.7 --description "New function" --timeout 10 --memory-size 1024 --timeout 60 --profile <your_account_ID>-lambda-profile --region us-east-1
Step 8. Point Kibana (or Drill. at your new table by executing this command in your terminal window, replacing <ARN_of_the_function> with your ARN value from Step 5, <your_account_ID> with your AWS account ID, <your_rpe_name> with your rpe name, and <your_table_name> with the name of your table.
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