Category: Analytics

Data within public blockchain networks such as Bitcoin and Ethereum can be accessed by anyone. However, accessing and making sense of this information has traditionally been a complex and technical undertaking. Much of the data is encoded and stored as bytes, rather than in a human-readable format. In this post, we introduce a solution that demonstrates how you can chat with blockchain data using Amazon Bedrock and the AWS Public Blockchain datasets. We discuss Amazon Bedrock, review the solution architecture, provide example prompts, share interesting findings, and go over how you can extend the solution to integrate with different data sources.

To query a Neptune database in Athena, you can use the Amazon Athena Neptune connector, an AWS Lambda function that connects to the Neptune cluster and queries the graph on behalf of Athena. In this post, we provide a step-by-step implementation guide to integrate the new version of the Athena Neptune connector and query a Neptune cluster using Gremlin and SPARQL queries.

In this post, we talk about how Infosys redefined the ETL landscape for their product sales and freight management application using Aurora zero-ETL to Amazon Redshift. We also explain our experience with the old process and how the new zero-ETL integration helped us effortlessly move data into a Redshift cluster for analytics along with metrics to monitor the health of the integration.

In this post, we discuss a design for a highly searchable movie content graph database built on Amazon Neptune, a managed graph database service. We demonstrate how to build a list of relevant movies matching a user’s search criteria through the powerful combination of lexical, semantic, and graphical similarity methods using Neptune, Amazon OpenSearch Service, and Neptune Machine Learning. To match, we compare movies with similar text as well as similar vector embeddings. We use both sentence and graph neural network (GNN) models to build these embeddings.

In this post, we explore how to transition from using Rockset to OpenSearch Service for your DynamoDB use-case effectively. To illustrate this integration, we consider a real-world example of a gaming company that tracks user interactions, such as in-game purchases and player scores, using DynamoDB. This data needs to be analyzed in real time to provide insights into user behavior, detect anomalies, and personalize the gaming experience.

In this post, we demonstrate how you can use Spring Cloud to interact with Amazon DynamoDB and capture table-level changes using Kinesis Data Streams through familiar Spring constructs. We run you through a basic implementation and configuration that will help you get started.

In this post, we demonstrate how to create a centralized monitoring solution using Database Activity Streams and Amazon OpenSearch Service to meet audit requirements. The solution enables the security team to gather audit data from several Kinesis data streams, enrich, process, and store it with retention to meet compliance requirements, and produce relevant alarms and dashboards.

In this post, we show how you can use AWS Database Migration Service (AWS DMS) to migrate relational data from Amazon RDS into compressed archives on Amazon S3. We discuss partitioning strategies for the resulting archive objects and how to use S3 Object Lock to protect the archive objects from modification. Lastly, we demonstrate how to query the archive objects using SQL syntax through Athena with seconds latency, even on large datasets.

A knowledge graph combines data from many sources and links related entities. Because a knowledge graph is a gathering place for connected data, we expect many of its entities to be similar. When we find that two entities are similar to each other, we can materialize that fact as a relationship between them. In this […]

In Part 1 of this series, we discussed the high-level architecture of multi-threaded full load and change data capture (CDC) settings to tune related parameters for better performance to replicate data to an Amazon Kinesis Data Streams target using AWS Database Migration Service (AWS DMS). In Part 2, we provided some examples of how we […]