Distributed Data Warehousing with Bacalhau
Expanso improves the efficiency of processing data in distributed environments. From small internet-of-things logs all the way up to petabyte scale transaction data and everything in between. With Expanso, leading organizations can architect, implement, and maintain enterprise-grade distributed compute platforms without the challenges of job orchestration and data synchronization across multiple locations.
Centralized data warehousing has challenges.
Difficulty in scaling and adaptingAs data and analytical demands grow, data warehouses become costly and complex, and hard to change based on different requirements
Performance degrades with more dataMore users and applications accessing the system lowers performance and delays important data analysis
Modifications and maintenance are expensiveUpdating and maintaining data warehouses is resource intensive; requiring skilled personnel, software and hardware
Distributed data warehousing can make a significant impact.
Instead of exclusively lifting and shifting all your data into a data warehouse, there’s another way. Move your compute to the data. This approach significantly reduces costs, enhances scalability, and ensures real-time access to critical insights.
Increase scale and improve security by adding relatively small compute nodes at data sources, and send only cleaned and secured results
Run immediate queries on the latest data without having to wait for it to be transported back to your central warehouse
Avoid being forced to use a single provider and pick the systems that best suit your needs at each data location
Expanso Adds a Distributed Data Warehouse to Your Modern Data Stack.
Expanso lets you build a distributed data warehouse without having to replace your current systems. And, by adding this layer, Expanso reduces costs and speeds time to understanding. Most companies already have the data and computing power they need at edge locations. And most of it has latent compute power that is not being used.
Expanso turns your existing compute resources into a dynamic data warehouse. Just install the flexible and lightweight software agent where your data lives, and you can run compute jobs on-site.
Expanso is compatible with Docker and WebAssembly so it is efficient at handling diverse workloads and natively supports the modern data stack out of the box, including Go, Rust, Java, Python, R, or just about anything you can think of.
Expanso significantly reduces data transfer costs by providing direct access to local data. It supports a variety of storage options including S3-compatible Object Storage, hosted APIs, and direct local storage. All of your data is ready for computation.
Expanso integrates with your existing systems and is designed to evolve with your business needs. No need to rewrite your entire data stack for significant improvements in security, cost, and speed.
We provide all this by based our platform on the Open Source Bacalhau Project
Implementation Example
Retail chains with multiple stores across different regions are looking for ways to improve real-time understanding and marketing opportunities many times a day. Each store has a POS system collecting customer and sales data but, traditionally, this data is batch-uploaded to a central data warehouse at the end of each day for processing and report generation. This leaves many campaigns and employees operating off stale, unreliable data for the majority of their day.
With Expanso, the retailer can add every store to their global compute network, and processes real-time data locally. Expanso orchestrates the execution of workloads across all locations, and ensures reliable, secure delivery of the findings both in-store and globally. Now, retailers can now query data in real-time as data is generated, producing instant insights, and enabling significant improvements to marketing and in-store spend.
Expanso automates the querying of new data as it is generated and deliver real-time insights to the people and systems that need it. Further, both real-time and batch uploads are integrated with your existing infrastructure such as Databricks Data Sharing, Snowflake, MongoDB, and other modern data stack tools.
By processing data locally, Expanso significantly reduces the amount of data that needs to be transferred over the network. It also reduces the need for additional data warehouse infrastructure, which oftentimes can be orders of magnitude more expensive than traditional compute.
Minimizing data transfer not only reduces the risk of data incursions, but it also ensures better compliance with data governance regulations which have many restrictions on the amount of Personally Identifiable Information (PII) which can move across legal boundaries. Further, every job executed on Expanso provides a full audit log of tasks that were executed, for further verification internally and to regulators.
Build it Yourself
For detailed instructions and code examples, visit our comprehensive documentation page.
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