Data ingestion pipelines

Delivering efficient Amazon Athena data pipelines

Fully-automated, code-free data pipelines to an optimized Amazon Athena and Amazon S3 data lake

Our Athena service automatically takes care of data lake formation, data catalogs, and operations for you.

Our code-free, zero administration data lake service delivers cost savings and performance gains for Amazon Athena by compressing, partitioning, and converting your data to a columnar format to reduce the amount of data that it needs to scan.

Amazon Athena is serverless, so there is no infrastructure to manage. With our automated data pipeline service you don’t need to worry about configuration, software updates, failures, or scaling your infrastructure as your datasets and number of users grow.

"Openbridge showed us how we can leverage new opportunities with data lakes. They helped us realize a cost-efficient, cross-cloud AWS data lake to Oracle architecture. We’re now tapping into a modern and innovative data stack with the help of the Openbridge plaform."

K. Tailor, Senior Enterprise Architect – AICPA | CIMA

Remove barriers to Amazon Athena

Focus on insights, not infrastructure with Amazon Athena serverless data lake

Amazon Athena supports a broad range of options for business intelligence and data visualization tools. As a result of our "analytics-ready" approach, our service ensures you are up and running faster with your favorite business intelligence, data visualization, SQL, or data science tools.

The Openbridge analytics-ready model maximizes investments in your preferred tools and the people that use them. We accomplish this by consistently embracing current and emerging standards-based for data access.

Applying industry best practice for our data ingestion, data engineering, and architecture ensures you have consistent and easy access to your data within leading tools like Grow, Tableau, Microsoft Power BI, or Looker.

Delivering "analytics-ready" Amazon Athena data

Code-free, Amazon Athena data ingestion pipelines for insights, analytics, and exploration

Use an incredibly diverse array of tools to explore, analyze, and visualize Amazon Athena data to understand business performance. Connect your favorite business intelligence, data visualization, SQL, or data science tools.

Need a customized plan tailored to your Amazon Athena needs?

We tailor plans designed for teams using Amazon Athena that generate large amounts of data, require custom data integrations, invoiced billing, or a professional-services agreement.

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Accelerate your aha moments

Data wrangling can be intimidating, leaving the complex data engineering work to us.


Free your team from painful data wrangling and silos. Automation unlocks the hidden potential for machine learning, business intelligence, and data modeling.

Unlock data silos


Use an incredibly diverse array of tools like Looker, Tableau, Power BI, and many others to explore, analyze, and visualize data to understand business performance.

Flexible data analytics tools


Realize incredible operational savings by leveraging fully automated, zero administration serverless data lakes and cloud data warehouses.

ELT & ETL automation

Athena Frequently Asked Questions

What are some aws athena use cases?

One of the popular uses cases is combining the simplicity of Tableau, a data lake and the power of Athena. This use cases demonstrates how to deliver a cost-efficient, high-performance analytics driven data lake architecture. Read more about this use case here: 4 Steps To Create a Serverless Analytics with Tableau and Amazon Athena


To maximize productivity, your data needs to be organized, processed, and loaded into a data lake, or warehouse. This data warehouse will act as a central repository of data aggregated from disparate sources. The data destination becomes the hub that allows you to plug in your favorite tools so you can query, discover, visualize or model that data.


You have a lot of powerful and affordable choices these days! Tools like Tableau Software, Looker, Mode Analytics, Chartio and Microsoft Power BI are just a few options to consider. Take a look at the full list of tools or read our DZone article about creating an objective 10-point business intelligence tool checklist to help narrow the field. If you have questions, feel free to reach out to us


No, there will not be any charges from Openbridge for your warehouse. Any charges are directly billed by the data destination provider (i.e. Google, Azure, or Amazon) to you.

Does AWS Athena pricing use on-demand costing?

Every data lake or cloud warehouse has its own pricing model. Often pricing will vary by usage, which is defined by the compute and storage consumed or provisioned. Depending on your situation and requirements, different price-performance considerations may come into play. For example, if you need to start with a no or low-cost solution, Athena only charges according to usage. This may provide you with the essentials to kickstart your efforts. If you have questions, feel free to reach out to us. We can offer some tips and best practices on how best to set up a warehouse based on your needs.


Yes! Amazon suggests that the use of partitioning can help reduce the volume of data scanned per query, thereby improving performance and reducing cost. You can restrict the volume of data scanned because partitions act as virtual columns. When you combine partitions with the use of columnar data formats like Apache Parquet, you are optimizing for best practices.


Yes, using standard SQL is supported for Athena. Most destinations, like Google BigQuery, Amazon Redshift, Amazon Athena and others support familiar SQL constructs. There may be some limitations or best practices for the specific use case, but the rule of thumb is that SQL is available.

DO YOU OPTIMIZE FOR Athena data lakes?

Yes! We follow Amazon's best practices relating to file sizes of the objects we partition, split and compress. Doing so ensures queries run more efficiently and reading data can be parallelized because blocks of data can be read sequentially. This is true mostly for larger files as well as smaller files, generally less than 128 MB, that do not always realize the same performance benefits.

Does amazon athena csv querying work?

Yes, you can query CSV. We have a service that automates loading of CSVs for use in Athna. However, using CSV is not the most efficient approach. DZone has published an article we wrote on the subject: Apache Parquet vs. CSV File.

Which data lake or cloud warehouse should I be using?

When it comes to building your data strategy and architecture, it's essential to understand which data warehouses should be candidates for consideration. Typically, teams will be asking themselves answers like "How do I install and configure a data warehouse?" or "Which data warehouse solution will help me to get the fastest query times?" or "Which of my analytics tools are supported?" This article covers key features and benefits of five widely used data lake and warehouse solutions supported by Openbridge to help you choose the right one: How to Choose a Data Warehouse Solution that Fits Your Needs. If you have answers, feel free to reach out to us.

Do I need an expert services engagement for Athena?

Typically, you will not need services for Athena. Most customers are up and running using their Athena data quickly. However, if you need support, we do offer expert services. There may be situations where you have specific needs relating to Athena data. These situations can require expert services to tailor Athena data to fit your requirements. Ultimately, our mission is helping you get value from data, and this can often happen more quickly with the assistance of our passionate expert services team.

Do I need to authorize Openbridge or its Partners my access to Athena system?

Yes, typically, Athena requires authorization to access your data. You would provide us with the Athena authorizations, so we can properly connect to their system. However, there are some situations where companies like Athena can "push" data to us. In those cases, we provide them with connection details to our API or our Data Transfer Service. Once they have those details, they use that information to connect, authenticate, and deliver data to us.


Yes! Amazon suggests compression and file splitting can have a significant impact to speed up Athena queries significantly. The smaller data sizes mean optimized queries, and it will also reduce network traffic with data stored in Amazon S3 to Athena. When your data is splittable, Openbridge will do this Athena optimization for you. This allows the execution engine in Athena to optimize the reading of a file to increase parallelism and reduce the amount of data scanned. In the case of an unsplittable file, then only a single reader can read the file. This only happens in the case of smaller files (generally less than 128 MB).


Yes! Amazon suggests the use of columnar data formats. We have chosen to use Apache Parquet vs other columnar formats. Parquet will store data efficiently with column-wise compression, including different encoding and compression, based on data type. Openbridge will automatically handle the conversion of data to Parquet format, saving you time and money, primarily when Athena executes queries that are ad hoc in nature. Also, using Parquet-formatted files means reading fewer bytes from Amazon S3, leading to better Athena query performance.

how does aws athena work

Athena use Presto, a commercialized version of a Facebook project. Presto is an open-source SQL query engine that powers the AWS Athena service. Unlike Presto, you only pay for the queries you run, no servers to manage. Check out the article What is Presto, Facebook Presto Database, PrestoSQL, or PrestoDB? A powerful SQL query engine

Is there a looker athena connection? How about for Tableau or Power BI?

Amazon does charge for the service. For the current costs, check out the AWS pricing page

does amazon athena cost extra

Amazon does charge for the service. For the current costs, check out the AWS pricing page

Where can I find Amazon Athena documentation?

Check out the AWS documentation.

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