Category: Amazon Athena

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 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.

It’s common in an enterprise for data that logically fits together to be separated into different databases. Some data is better suited for one storage than another, and it may not be feasible to locate all your data in one data store. But this data often needs to be linked back together to provide a […]

While databases are used to store and retrieve data, there are situations where applications should archive or purge the data to reduce storage costs or improve performance. However, there are often business requirements where an application must query both active data and archived data simultaneously. Developers need a solution that lets them benefit from using […]

Many industries are taking advantage of the Internet of Things (IoT) to track information from and about connected devices. One example is the energy industry, which is using smart electricity meters to collect energy consumption from customers for analytics and control purposes. Vector, a New Zealand energy company, combines its energy knowledge with Amazon Web […]

Amazon Quantum Ledger Database (Amazon QLDB) is a fully managed ledger database that maintains a complete, immutable record of every change committed to the database. As transactions are committed to the database, they are appended to a transaction log called a journal and are cryptographically hash-chained to the previous transaction. Once committed, the record of […]

In this post, we share an open-source solution for running cross-chain analytics on public blockchain data along with public datasets for Bitcoin and Ethereum available through AWS Open Data. These datasets are still experimental and are not recommended for production workloads. You can find the open-source project on GitHub here and the public blockchain datasets […]

Customers have asked for a way to interact with graph datasets in Amazon Neptune using business intelligence (BI) tools such as Amazon QuickSight. Although some BI tools offer generic HTTP connectors that allow you to define a set of REST API calls to extract data from REST endpoints, you have to predefine either Gremlin or […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. With the announcement of Amazon CloudWatch Metric Streams, you can now stream near-real-time metrics data to a destination such as Amazon Simple Storage Service (Amazon S3). Metric Streams supports two primary use […]