# Aurora PostgreSQL
## Amazon.com
"Implementing and scaling hundreds of on-premises instances across the database fleet consumed all database team member resources for many weeks and was a relatively low value-add task for database administrators. In the Oracle world, a seemingly simple change such as scaling from a medium to a large database instance required provisioning hardware, standing up primary and standby databases, and managing failover during transitions, which could take a full day for each instance. Not to mention the fact that we were using specialized hardware that had to be ordered months in advance. After migrating to Amazon Aurora, provisioning additional capacity is achieved through a few simple mouse clicks or API calls."
Brent Bigonger, Senior Database Administrator - Amazon Fulfillment Tech
[Watch the video >>](https://www.youtube.com/watch?v=gt9GSw7UGl4&refid=em_a134p000006vl9zAAA)
## Amdocs
"Prepping and getting a database cluster up and running took three weeks for installing, confirming network, testing for latency. On Amazon Aurora we're now able to effectively do it in a day."
Jay Deen, CTO - Amdocs Media
[Read the case study >>](https://d1.awsstatic.com/asset-repository/AWS_MarketOne_CaseStudy_020262020.pdf)
## Best Western International, Inc.
"The hotel industry is rapidly changing, as more customers expect the ease and convenience of mobile computing. Moving to AWS brings our organization to the forefront of innovation and allows us to give our guests fast, reliable and secure data processing so they can organize their trips, change their reservations, and book their stay with us."
David Kong, President & CEO - Best Western
## Bio-Rad Laboratories
"Our Unity Next Peer Quality Control (QC) solution provides labs with instant, centralized access to peer reporting through an intuitive platform. By simplifying access to QC insights, we empower labs to refine their processes, mitigate errors, ensure regulatory compliance, and prioritize patient safety with confidence. To address key challenges—driving product adoption, educating users on features, and supporting multiple languages— Bio-Rad enables customers to engage with a chatbot that references product and user manuals to deliver answers directly from these documents, complete with feature-specific image references. We wanted to build a generative AI solution aimed at enhancing our support services and speeding up product feature education and adoption.
We turned to AWS and built our Retrieval-Augmented Generation (RAG) solution leveraging Amazon Aurora PostgreSQL-Compatible Edition with the pgvector extension, integrated with Amazon Bedrock using the Claude V3 Haiku LLM, Amazon Titan Embeddings text models, and AWS Translate to facilitate multi-language support for 14 different languages in Unity Next Peer QC. Unlike traditional support methods, our chatbot leverages product and user manuals to deliver precise answers, complemented by feature-specific visual references. This approach reduces reliance on support teams while accelerating user education. With this innovation, we see a 20% reduction in customer call volume and improved feature adoption, driving better outcomes for labs worldwide."
Jasmina Desai, Associate Director, Software Architecture and Development - Bio-Rad Laboratories
## BMC
"The idea of having a company like Amazon Web Services stand behind an open source product and take care of important attributes like high availability, scaling, and overall data management is huge. Amazon Aurora provides the open source database management layer we've been seeking."
Raj Cheruvu, AVP R&D, Helix ITSM - BMC
[Read the case study »](https://d1.awsstatic.com/rdsImages/AWS_BMC%20Case%20Study_FINAL.pdf)
## BMLL Technologies Ltd
"Amazon Aurora PostgreSQL is helping us solve performance and scalability challenges to provide deeper and faster data analysis to our customers. In addition, the built-in security, durability, and high availability capabilities of Aurora PostgreSQL help to simplify and automate most of our DBA requirements, lowering our costs while increasing reliability."
Dr. David Robinson, CTO - BMLL Technologies
## British Airways
"Thanks to Amazon Aurora serverless and Data API, we can now parallelise our data analysis and processing within AWS Lambda. Instead of executing our data science workloads sequentially, we can run them concurrently. Lambda can seamlessly scale from zero to 200 or 300 functions running concurrently, and the Data API efficiently manages connection spikes. Consequently, data analysis for a single flight is now typically completed in less than 30 seconds, a significant improvement from the tens of minutes it used to take."
Nils Mohr, Senior Flight Data Software Engineer - British Airways
## Cloudability
"Amazon Aurora has become the database of choice for all our MySQL workloads. Our True Cost Engine delivers cost efficiency to customers, using a new predictive model based on petabytes of customer cost optimization data. To support this kind of analysis, we need a database that is performant, scalable, cost-effective, and easy to maintain and tune. Aurora solves our biggest issues with managing large, production databases with strict SLAs. Now that PostgreSQL is supported, we expect all our PostgreSQL workloads to move to Aurora as well."
Matt Finlayson, Vice President of Engineering - Cloudability
## CloudZero
"Amazon Aurora serverless and Data API enable us to avoid managing complex VPC's and network access controls which significantly reduces our operational complexity and security burden. This means being able to focus on hiring more software engineers and less operations folks. We think of this as living the "Serverless lifestyle" where we rely on AWS for ensuring our uptime and availability which allows us to move faster with less headcount costs."
Erik Peterson, CTO/CISO & Founder - CloudZero
## CORTO
"We began using Amazon Aurora PostgreSQL-Compatible Edition with the pgvector extension in 2023 as part of CORTO's AI-powered legal technology platform, which helps lawyers achieve faster and more effective results by automating legal tasks. With pgvector and HNSW indexing, we can store, index, and query high-dimensional embeddings to power semantic search across more than 2.5 billion documents. These capabilities allow us to deliver highly relevant insights in milliseconds while keeping our entire data stack within AWS, simplifying operations, strengthening compliance, and improving performance. The scalability with Aurora has allowed us to seamlessly manage fast-growing datasets, including 46 terabytes of data in our APAC cluster and 7.6 billion vectors in our primary embeddings table. By consolidating both relational and vector workloads in a single high-performance environment, we've significantly reduced infrastructure complexity and accelerated product development."
Anisa Dean, Senior DevOps Engineer - CORTO
## DriveWealth
"After DriveWealth successfully migrated the production workload from CockroachDB to Aurora PostgreSQL, we improved our read/write throughput up to 5X, enhanced data consistency, and achieved an 80% cost reduction. We were impressed with the AWS team's ability to resolve our challenges from working with previous vendors – they earned our immediate trust by recommending Aurora."
Venkat Vadlamudi, Engineering, Data & Analytics Leader - DriveWealth
## Decisiv
"Aurora PostgreSQL is instrumental for Decisiv as we upgraded our infrastructure to support the growing scale, performance and reliability requirements that our customers expect. We've consolidated multiple SQL Server instances into a single database that boasts higher performance at a better cost. Thanks to Aurora, our migration from SQL Server to PostgreSQL went more smoothly than we anticipated, and we are now well-positioned to rapidly scale."
Satish Joshi, CTO - Decisiv
## Easygo
"The highly variable nature of these sport-seasons workloads meant Easygo saw a rapid scale increase on top of its usual traffic patterns. We wanted the engineering team to spend less time managing database scaling requirements, and a database solution that could seamlessly scale to handle sporting events worldwide in different time zones. Easygo migrated roughly 50 databases over to Amazon Aurora serverless, enabling the team to focus on building bigger and better games, while spending less time investigating bottlenecks."
Director of Engineering - Easygo
## Emma
"At Emma, we're focused on thoughtful product design and friendly expert services to help marketers do their very best work. We manage several multi-terabyte OLTP databases that process nearly 300 million transactions per day. Aurora PostgreSQL provides us with a highly performant, secure, and more scalable database cluster than we are able to affordably create in a traditional datacenter. Aurora PostgreSQL also allows us to be much more responsive when meeting expected business growth demands for the foreseeable future, all while reducing the time needed to manage, maintain, and scale the database systems."
Marc Powell, Director of Infrastructure - Emma
## FireEye
"With Amazon Aurora, we were able to bring Detection On Demand to the market in a matter of months thanks to its serverless architecture and fully managed database services."
Martin Holste, CTO Cloud - FireEye
[Read the case study](https://d1.awsstatic.com/rdsImages/AWS_FireEye_CaseStudy_FINAL.pdf) and [watch the video >>](https://www.youtube.com/watch?v=WuZ3DMHZ40U)
## Guidewire Software
"Compared to commercial databases, we observed similar or better performance at the 90th percentile. But at the 99th percentile, we saw even better response times."
Kevin De Yager, Senior Product Manager for InsuranceSuite Cloud - Guidewire
[Read the case study](https://d1.awsstatic.com/rdsImages/AWS_Guidewire_CaseStudy_FINAL.pdf) and [watch the video >>](https://www.youtube.com/watch?v=CLKP4KyyPAo)
## Globe Telecom, Inc.
"The shift out of Oracle will save us an estimated $1 million over the next three years in licensing fees—funds that Globe Telecom can use for new digital transformation projects. Performance has been solid—exceeding the latency target of 40 milliseconds."
Melissa Banzon, Head of ISG Transformation Office - Globe Telecom
## Goldsky
"Goldsky delivers blockchain data to leading stablecoin issuers and fintechs requiring sub-second freshness for payments, treasury, and compliance. Our real-time platform ingests 20\+ million events per second from 120\+ networks into Amazon Aurora PostgreSQL, the backbone of our streaming pipeline. Aurora handles our heavy write velocity — over 100,000 commits per second at peak and \~50,000 sustained 24/7 — with bulk inserts of stablecoin transfers and on-chain transactions driving 1M\+ write IOPS and 1.5M\+ read IOPS at peak. With Aurora read replicas, we can serve low-latency queries to hundreds of customer applications across \~8,000 concurrent writer connections, while transactional semantics handle chain reorganizations atomically, ensuring fintechs never see stale or inconsistent ledger data.
Aurora auto scaling means we never pre-provision capacity as our customers expand into new networks or payment corridors. With Aurora I/O-Optimized, we get cost predictability as our transaction volume grows, meeting high-TPS workloads in a way no alternative we evaluated matched. We now run our streaming engine at billions of messages per month, scale that would be unmanageable on self-hosted PostgreSQL, delivered on Aurora PostgreSQL with operational excellence that stablecoin issuers and regulated fintechs require. With Aurora PostgreSQL our small engineering team operates at massive scale without dedicated database administrators, so we can focus on building the data infrastructure that powers the next generation of stablecoin and financial applications, not on managing infrastructure ourselves."
Jeff Ling, CTO - Goldsky
## INRIX
"From raw GPS points, INRIX generates large-scale vehicle movement data and ingests the data into sharded Amazon RDS for PostgreSQL instances. We are hitting the storage and performance limits per shard and looking for a more scalable solution. With Amazon Aurora's compatibility with PostgreSQL, we've seen three times performance improvements in our benchmarks. We love Amazon Aurora's ability to scale storage independently of computing resources at better price points."
Trang Nguyen, Senior Software Engineer - INRIX
## Intuit
"Looking to reduce operational overhead and improve our database costs, we decided to utilize Amazon Aurora serverless. Mixed-configuration clusters are perfect for our use case, which allows us to use a combination of provisioned Amazon Aurora writer and Amazon Aurora serverless readers within the same cluster. With Aurora serverless, we get the benefits of automatic scaling without compromising on our requirement for high availability and disaster recovery. We use Aurora serverless in both our production and non-production environments, and it has helped us save approximately 55% on our database provisioning costs. With Aurora serverless, our developers can focus more on building features and less on managing capacity."
Rajesh Saluja, Principal Data Engineer - Intuit
## LeadSquared
"As our customers started demanding faster onboarding of our chatbot, we wanted our chatbot solution to offer an easy setup, provide a personalized experience (based on customer specific data and intent), and automate repetitive tasks better. The integration of Retrieval-Augmented Generation (RAG) capabilities using Amazon Aurora PostgreSQL with the pgvector extension and LLMs available in Amazon Bedrock has empowered our chatbots to deliver natural language responses to out-of-domain inquiries, enhanced dialogue management, and reduced our manual efforts. With RAG, we can retrieve data from outside the LLM, for example from the website, knowledge base, or help documentation, and augment the prompts by adding the relevant retrieved data in context. RAG capabilities have made our chatbot better by allowing the system to provide natural language answers to questions that aren't in or a variation of the intent list. Consequently, we have observed a 20% improvement in customer onboarding times."
Prashant Singh, COO & Cofounder - LeadSquared
## MoeGo
"MoeGo is a SaaS provider offering all-in-one solutions that include business management, customer communication, and digital payments. As such, we use a multi-tenant architecture and face significant traffic fluctuations. We have adopted Amazon Aurora serverless across our core business scenarios, including appointment management, financial processing, and CRM to address our business need of 10x traffic variation between peak and off-peak hours. We leverage Aurora serverless for its exceptional elastic scaling capabilities to achieve intelligent adaptive allocation of database resources, significantly reducing our manual operational overhead and enabling our team to focus on product innovation and business development. Aurora serverless has a pay-as-you-go model, which has delivered 30% cost savings compared to traditional peak-capacity fixed instances, providing both a flexible technical foundation for global expansion and continuous delivery of high-quality digital services to our customers."
Zihao Yin, Platform Engineering Lead - MoeGo
## New Innovations
"Thanks to AWS and Amazon Aurora PostgreSQL, our company has been able to build an infrastructure that scales to meet our customers' demands. We found that Aurora PostgreSQL is a drop-in replacement for Amazon RDS PostgreSQL, with a few very important improvements: write throughput and automatically-expanding storage. We migrated 700\+ instances of Microsoft SQL Server, and LOVE the simplicity of management that Aurora PostgreSQL provides. Gone are the days of dealing with tuning and tweaking configuration files for optimal performance."
Stephen Sciarini, IT Manager - New Innovations
## Nielsen
"In our testing of Amazon Aurora PostgreSQL in the preview, we have seen very good performance upwards of 7-11 times that of RDS PostgreSQL, for both write and read/write workloads. We are also excited about the expected scalability and reliability, giving us great confidence that Amazon Aurora PostgreSQL will meet our requirements as we move some of our core database workloads to AWS."
Todd Lightbody, Watch Architecture Leader - Nielsen
## ProQuest
"We've gotten so many benefits from migrating our database from Oracle to Amazon Aurora such as high availability and easier scaling for reads. All of these benefits come out of the box and at a lower cost and with far less licensing complexity. For data migration, we used the AWS Database Migration Service (DMS). It only took 24 hours to migrate 1.25 Terabytes of data with our first attempt. We worked with the AWS team who helped us experiment with parallelization and organizing the migration by breaking it down to multiple tasks to get the final production data migration down to four and a half hours\!"
Suresh Karri, Director of Technology - ProQuest
## RavenPack
"We are enhancing our products by incorporating new heavily structured data such as market consensus estimates, products relationships, and supply chain information, to name a few. Many of our analytics apps have to access this data in real-time and maintain point-in-time sensitivity, which requires a fast performing and heavily relational database, resilient to failures, and distributed across multiple AZ's. In our testing, Aurora PostgreSQL has performed significantly faster than standard PostgreSQL, and has shown high compatibility with standard PostgreSQL. Given that we already have a deep usage of Amazon Redshift, and we are used to PostgreSQL interfaces, Aurora PostgreSQL will perfectly fit into our system."
Jason Cornez, CTO - RavenPack
## ResultsCX
"We moved from SQL Server to using Amazon Aurora PostgreSQL as an Enterprise Data Store (EDS) and have continued to expand its reach within the business. Building our EDS in Aurora PostgreSQL allowed us to reduce complexity through automation and consolidation, while producing more accurate and stable reports for business users. It also allowed us to substantially reduce our licensing costs as Aurora PostgreSQL is an open-source solution. Finally, the high availability and disaster recovery capabilities of Aurora PostgreSQL help us to deliver on the SLAs that our business users expect.
The ability to retrieve data at a high speed for developing ad-hoc analysis for near real-time issues has increased our speed to customer, vastly. We can now identify valuable insights over larger data sets, instead of selected sampling, utilizing Aurora PostgreSQL. We have been able to reduce our total number of reports from 3,000 to 1,000, decrease time spent managing the legacy reporting platform by 30 percent, and, most importantly, resource time spent on manual reporting historically is now being utilized to develop valuable skills in other areas that provide higher value for career development."
Dr. Jim Sullivan, Vice President Information Systems & Enterprise Applications - ResultsCX
## RocketReach
"Our team has enjoyed the scalability benefits of Aurora PostgreSQL, which has allowed us to quickly ingest significant amounts of data without negatively impacting customers. The addition of the Amazon Aurora I/O-Optimized feature has stabilized our daily costs at RocketReach, reducing our total monthly Aurora costs by 60% and allowing our team to focus on business priorities rather than cost management efforts. We are now able to reap the scalability benefits of Aurora without having to worry about cost increases as our traffic scales.
Aurora I/O-Optimized was a critical addition for our team at RocketReach, not only did it allow us to leverage the advantages of Aurora more economically, it also helped prevent unplanned work across our teams. We will absolutely continue to leverage Aurora I/O-Optimized when the use case aligns with its capabilities. At RocketReach, we have many workloads that require substantial amounts of data to be processed efficiently while maintaining performance for our customers. For these use cases, Aurora I/O-Optimized allows us to balance cost and performance, while rapidly delivering value to our customers."
Jeremy Livingston, CTO - RocketReach
## Shippo
"Our service is 24/7 and our transactional database is highly critical such that any unavailability will result in service downtime. We wanted to upgrade our PostgreSQL database to Aurora, but the traditional upgrade approach required a two-step process, with each step resulting in a multi-hour outage - far too much impact to our business and customers. Looking to the unconventional, we explored using AWS DMS for the upgrade. After completing a very positive POC with outstanding support from AWS DMS team, we decided to go ahead with DMS and were able to skip the intermediate PostgreSQL versions and migrate directly to Aurora. DMS was stress-free and reduced our upgrade downtime to minutes. Post-upgrade, Aurora has proven to have better availability, performance, and scalability which gives us the comfort that we can continue to support Shippo's rapid growth."
Calvin Xu, Data Architect - Shippo
## SBI Sumishin Net Bank
"We are an internet-only bank based in Japan. Our databases are critical to our ability to provide excellent personal banking and investment services. Since we migrated from Oracle RAC to Amazon Aurora, we have cut our database management costs by 83% while also getting 50% better performance. We've benefitted from improved speed, availability and scalability."
Shinichi Aikawa, Director of System Development 2 - Sumishin SBI Net Bank
## SRA OSS
"In our performance testing of Amazon Aurora's PostgreSQL compatibility, we found that the performance was three times better than standard PostgreSQL. Our testing also showed that Amazon Aurora is fully compatible with PostgreSQL 9.6, and we believe customers will be able to move large enterprise workloads from on-premises commercial databases to Amazon Aurora because of its high performance, high availability, and PostgreSQL compatibility. SRA OSS will add support for Amazon Aurora to the next version of pgpool-II, which provides clustering management middleware for PostgreSQL."
Tatsuo Ishii, Japan President - SRA OSS, Inc.
## SurveySparrow
"At SurveySparrow, we operate five business units powered by agentic AI integrated throughout our product stack. Our newly launched agentic AI-driven customer experience capabilities for customer support and sales demanded high-performance vector search capabilities combined with seamless transactional data access—making the database layer mission-critical. We migrated from standalone vector databases like Pinecone to Amazon Aurora PostgreSQL with pgvector, consolidating both vector embeddings and relational data into a unified database platform. This architectural shift eliminated the complexity of managing separate systems while delivering the performance and scalability our AI agents require. It gave us immediate wins: no cross-service hops, simpler architecture, and deeper integration with AWS services. With Aurora serverless, we have cut costs by nearly 50% and improved query latency by an estimated 30% for our agentic AI use cases. Storing embeddings and metadata in the same tables has made our design cleaner, and auto-scaling handles our spiky AI workloads without any manual effort. The best part is our teams can focus on building better AI, not juggling multiple databases, while our customers benefit from faster, more cost-efficient experiences."
Jagadeesh Rajarajan, Head of AI - SurveySparrow
## Tenable
"Tenable relies on AWS to provide the flexibility and scalability needed to run its large-scale Tenable.io vulnerability management platform. Thanks to Aurora, Tenable can more easily handle large and complex unscheduled queries from customers in seconds without breaking the bank, unlike with standard PostgreSQL instances. Aurora's cost model for IO and storage means Tenable's usage and costs are correlated. Plus, what previously took 10\+ minutes on a similarly sized RDS instance takes a few seconds on Aurora, and in cybersecurity, every second counts. Tenable uses Aurora for workloads with large-scale unpredictable queries, and ultimately, Aurora enables Tenable to better serve our customers."
Scott Hirleman, Cloud Infrastructure Cost Manager - Tenable
## TIBCO
"We are an early adopter of Amazon Aurora PostgreSQL and used the AWS Database Migration Service to transition TIBCO Cloud Live Apps to Amazon Aurora seamlessly, while it was in production, without our customers noticing any interruption in our service. Amazon Aurora's reliability, security, and fast failover will continue to help us scale Live Apps, giving customers constant access to our service so they can build and run apps quickly and with high availability."
Matt Quinn, Chief Operating Officer - TIBCO
## Tokio Marine & Nichido Fire Insurance
"We applaud AWS for providing the extended support for Amazon Aurora and Amazon RDS. AWS is a company that listens to the voice of user companies and makes them come true. This is one of the biggest reasons we use AWS. We want to continue to strengthen our partnership for mutual growth and development."
Hiroki Yamashita, Manager - Tokio Marine & Nichido Fire Insurance Co., Ltd.
## Verisk Analytics, Inc.
"We moved our Oracle and SQL databases to Amazon Aurora to improve the speed, latency, and processing times of our databases. The databases migration to Aurora PostgreSQL took less time and resources than we anticipated. Verisk 3E has compliance and performance requirements from our customers to run 3E Insight in various regions globally. Thanks to Amazon Aurora, we can now deliver a highly responsive, scalable, and highly available intelligent compliance solution to our worldwide customers. The migration gave us a significant cost reduction and improved our ability to deliver value to our customers."
Ashish Verma, Sr. Director of Software Engineering - Verisk 3E
## Verizon
"Verizon is helping our customers build a better, more connected life. As part of this journey, we are undergoing a major transformation in our database management approach, moving away from expensive, legacy commercial database solutions to more efficient and cost-effective options. Testing of Amazon Aurora PostgreSQL showed better performance over standard PostgreSQL residing on Amazon EC2 instances, and the AWS Database Migration Service and Schema Conversion Tool were found effective at identifying areas for data-conversion that required special attention during migration."
Shashidhar Sureban, Associate Director, Database Engineering - Verizon
## Vindicia
"Beyond defraying the costs, the move to AWS makes the tedious on-premises jobs we worry about go away. We look forward to using the capabilities of Amazon Aurora to access data more efficiently."
Steven Azar, Senior Manager of Data Programs - Vindicia
[Read the case study »](https://d1.awsstatic.com/asset-repository/AWS_Vindicia_CaseStudy_03032020.pdf)
## Wappa
"To help our customers reduce corporate travel expenses, our platform needs to find rides quickly and accelerate the budgeting, payment, and reporting processes. Since migrating our Oracle database to Amazon Aurora, our user validation process has become 60 percent faster, reporting time per user has dropped 75 percent, and the payment process is 70 percent faster. We're clearly seeing the results in our user growth numbers and user satisfaction ratings of our application."
Cesar Matias, Chief Technology Officer - Wappa
## Xata
"Xata has customers that require tenant isolation and want to build AI-driven applications that deliver low latency, highly relevant vector similarity searches to their users. In one particular case, Xata migrated a customer from Pinecone to using Amazon Aurora PostgreSQL-Compatible Edition with pgvector and realized a 65% cost reduction while meeting our query latency targets and providing additional functionality by being able to store the metadata in the same tables as the vector data. This resulted in a significant simplification of their application architecture."
Monica Sarbu, CEO & Founder - Xata