USE CASE: OPERATIONAL ANALYTICS
Power real-time analytics and transactional operations over unified business data—simultaneously, with zero performance degradation.
THE CHALLENGE
Avoiding performance bottlenecks
Delivering timely, tailored experiences to your customers often requires operational analytics, where real-time data from multiple sources are combined to drive operational efficiency. For example, healthcare organizations look to provide better patient outcomes by running real-time diagnostics simultaneously with batch jobs to access patient records. This leads to performance bottlenecks and creates issues with latency and accuracy as ETL processes struggle to keep up with real-time updates.
OUR SOLUTION
Real-time access to accurate data
Analytics Accelerator from EDB Postgres AI enables high-performance analytical and transactional queries over the same data without disrupting business operations. By separating compute from storage, employing a vectorized query engine, and unifying analytical and transactional stores in Postgres, you get real-time access to accurate data—and EDB Postgres AI's seamless integration with efficient object storage keeps costs in check as you scale.
Vectorized query engine
EDB separates storage from compute and employs an upgraded query engine that is optimized for columnar data formats, allowing hot and cold data queries to run 30x faster compared to standard Postgres—providing businesses exceptional analytical performance without impacting transactional workloads.
Unified data management
By bringing both analytical and transactional workloads together within Postgres, EDB reduces the need for complex ETL pipelines, minimizes data fragmentation, and reduces reliance on external systems. This unified approach ensures consistent, real-time access to data and improves overall operational efficiency.
External lakehouse ecosystem integration
Handle growing data volumes by seamlessly integrating Postgres with cost-efficient object storage in the lakehouse ecosystem—so you can use standard SQL to write lakehouse tables to external object storage and query them just like any Postgres table.
DEMO
DEMO
Improve Analytics Insight without Sacrificing Performance
Improve Analytics Insight without Sacrificing Performance
With Analytics Accelerator powering operational analytics, organizations achieve faster queries, streamlined workloads, and scalable infrastructure—resulting in more responsive business intelligence, lower costs, and greater resilience.
Better performance
EDB's vectorized query engine powers 30x faster analytical queries, on average, compared to native Postgres without degrading transactional performance.
Improved efficiency and consistency
Consolidate analytical and transactional workloads in Postgres with fewer systems for your teams to manage—and fewer complex ETL processes that can lead to inconsistency. Plus, lakehouse tables are 5x smaller on disk than Postgres tables and indexes, and object storage is 18x as cost-effective as SSD storage.
Seamless scalability
The natural scalability of Postgres and integrations with cost-effective object storage enable businesses to handle growing data volumes and increasing query complexity, ensuring the system is available and responsive as the organization scales.
EDB Postgres AI enables operational analytics
Analytics Accelerator automatically replicates transactional data to a separate analytics node. The vectorized query engine then queries replicated data and lakehouse tables seamlessly—without impacting ongoing operational workloads.
Related Products and Solutions
EDB Postgres AI
A modern Postgres data platform for powering mission-critical workloads from edge to core.
EDB Analytics Accelerator
Unlock rapid analytics in Postgres with the PGAA extension.
EDB Postgres in Public Cloud
Deploy self-hosted EDB Postgres AI in your cloud of choice.
EDB Postgres Distributed
Up to 99.999% uptime and 5x throughput performance versus native logical replication.
Resources
EDB Mission Control: A Postgres Lakehouse Innovation
Transforming Real-Time Analytics and AI Workloads with PostgreSQL
Unleashing AI with PostgreSQL: What is a Lakehouse?
Elevating Postgres Security with the EDB Trust Center
Operational analytics involves running simultaneous transactional and analytical queries on the same data to enhance business operations. EDB simplifies this by separating compute from storage and using a vectorized query engine, allowing high-performance analytics without impacting transactional workloads. Plus, by unifying analytical and transactional data within Postgres, EDB enables accurate, real-time insights and scalable infrastructure.
Some terms that can be synonyms for operational analytics are: real-time analytics, hybrid analytics, live analytics.
EDB addresses performance bottlenecks by separating compute from storage and using a vectorized query engine optimized for columnar formats. This ensures that high-performance analytics can be conducted without impacting ongoing transactional workloads, allowing businesses to process transactions and run analytics in real-time without degradation.
EDB unifies both analytical and transactional workloads within Postgres, reducing the need for complex ETL pipelines and minimizing data fragmentation. This unified approach ensures consistent, real-time access to accurate data, which improves the reliability of analytics and decision-making.
Key features include:
- Unified transactional, analytical, and AI data management
- Seamless lakehouse ecosystem integration
- Vectorized query engine
- Enterprise-hardened Postgres (secure, scalable, ACID compliant)
- Broadly compatible open source foundation
- On-premises, private cloud, or hybrid deployment options
Benefits include:
- Simplified data management
- 30x faster analytical queries compared to standard Postgres
- Greater cost efficiency (object storage is 18x cheaper than SSD storage, lakehouse tables 5x smaller on disk compared to Postgres tables and indexes)
- Seamless scalability
- Greater security and control
EDB Postgres AI integrates with any Postgres source, anywhere. It also integrates with flexible storage locations that are up to 18x more cost-efficient versus solid state drives—including Amazon S3, MinIO, or the local filesystem—and leverages the standardized Delta Table open table format, making it compatible with other tools and services across the lakehouse ecosystem.
EDB’s solution reduces the need for multiple systems and complex ETL processes, which lowers infrastructure, maintenance, and development costs—ultimately resulting in reduced operational expenses.
EDB optimizes storage costs with a combination of columnar lakehouse tables—which are 5x smaller on disk compared to Postgres tables and indexes—and object storage—which is 18x cheaper than SSD storage. This allows businesses to reduce overall storage expenses without sacrificing query performance.